Reaction Wheel

Midas List Feeder Firms

noreply@blogger.com (Jerry Neumann) — Thu, 09 May 2013 03:16:00 +0000

The Forbes Midas list just came out today. But it doesn't answer the question I know you have: who do you know that can get Jim Breyer to take a look at your go-go somoloco robofoto co?

We at Neu VC decided to help you out. We scoured the Crunchbases to find out which investors coinvest with or invest prior to the Midas List investors' firms. You can think of these firms as the Midas List feeder firms.

The firms are ranked by the percentage of the companies they invested in over the past five years that a Midas List firm invested in at the same time or later.

	Fund	% Midas
1.	Collaborative Fund	86%
2.	Glynn Capital Management	82%
3.	Felicis Ventures	81%
4.	XG Ventures	81%
5.	Thrive Capital	80%
6.	PivotNorth Capital	78%
7.	Forerunner Ventures	77%
8.	Start Fund	76%
9.	Lerer Ventures	76%
10.	Red Swan Ventures	75%
11.	Version One Ventures	75%
12.	DAG Ventures	73%
13.	High Line Venture Partners	71%
14.	Freestyle Capital	71%
15.	Founder Collective	69%
16.	O'Reilly AlphaTech Ventures	68%
17.	SoftTech VC	67%
18.	Tekton Ventures	67%
19.	Cowboy Ventures	67%
20.	Morado Venture Partners	67%
21.	CrunchFund	66%
22.	MuckerLab	63%
23.	Harrison Metal Capital	62%
24.	Northgate Capital	60%
25.	Phenomen Ventures	60%
26.	NextView Ventures	59%
27.	Neu Venture Capital	57%
28.	Kapor Capital	57%
29.	ENIAC Ventures	57%
30.	TriplePoint Capital	57%
31.	Radar Partners	57%
32.	Spring Ventures	57%
33.	A-Grade Investments	56%
34.	Data Collective	56%
35.	Trilogy Equity Partnership	55%
36.	Advancit Capital	55%
37.	Quest Venture Partners	54%
38.	Thomvest Ventures	53%
39.	Transmedia Capital	53%
40.	Helion Venture Partners	53%
41.	Vulcan Capital	53%
42.	Correlation Ventures	52%
43.	IA Ventures	52%
44.	Jafco Ventures	50%
45.	MentorTech Ventures	50%
46.	Silverton Partners	50%
47.	White Star Capital	50%
48.	Graph Ventures	50%
49.	Amicus Capital	50%
50.	Mohr Davidow Ventures	49%
51.	General Catalyst Partners	49%
52.	Google Ventures	48%
53.	Sutter Hill Ventures	48%
54.	Maveron	48%

The usual caveats: the data from Crunchbase is woefully incomplete. It doesn't include all deals. It doesn't have most angel investors, who might be the best way to get to some of these firms (because of the spotty angel coverage I decided to exclude anyone Crunchbase did not consider a 'financial organization,' so almost all angels are not on the list.)

I excluded firms that were primarily life sciences/biomedical and firms that invested primarily in non-US companies. I looked at investments for the last five years and weeded out firms that made fewer than five initial investments in that period or fewer than three in the last year.

I'm sure there's some signal in here, but there's also a ton of noise. Treat it as entertainment. There are many explanations for why these firms are here and others are not. Some good, some eh. For instance, note that Google Ventures is number 52; Google Ventures is making some solid bets and adding a ton of value. Why are they 52? I don't know.

Also note that the 40 firms from the Midas List that were used to generate this list are not themselves on the list. So, if you're like "why isn't SV Angel here?" the answer is that they are on the Midas List itself.

You Can't Learn from Failure, You Can Only Learn from Success

noreply@blogger.com (Jerry Neumann) — Mon, 29 Apr 2013 15:02:00 +0000

I feel strongly about not criticizing entrepreneurs. It's hard enough to start a company without the peanut gallery razzing you. And really, what good are you doing by being critical? Companies that are going to fail are going to fail without you wishing it on them, while your criticism might hurt companies that are on the path to success. What is constructive about your criticism?

The rationalization I always hear, from people who I suspect simply enjoy blood-sport, is: "how can we learn unless we look at what people are doing wrong?"

The easy answer is that there's a difference between a good post-mortem and criticizing something while people are trying to make a go of it. And there's a difference between a good post-mortem and 20/20 hindsight. The only person who can credibly make that distinction is the founder. Anyone else would have the unavoidable whiff of smugness.

There's a better answer and I think this is important. It's that criticism of failed companies is never very useful. Never.

You don't learn from failure. You can't learn anything from failure.

Ok, Neumann, you say. I have learned from failure. That time I burned my toast I learned to set the toaster lower. Now I don't burn my toast. Ha.

When I was a kid I wrote a computer program that learned to win at tic-tac-toe. First it build a decision tree of every possible tic-tac-toe game. Then it played you. Every time it lost it pruned that branch of the tree until only the wins or draws were left. It learned from failure.

Try that with checkers. Harder.

Try that with chess. Hard to impossible.

Try it with starting a company.

Any complicated system is too complicated to learn from failure. Yes, you can learn a few tricks, like: "don't spend all your money on fancy chairs" or "don't hire your college drinking buddies as EVPs of Business Development." But you can also spend your life learning about every mistake every startup founder ever made in all of recorded history and I guarantee that when you start your company you will discover all new mistakes to make. That is how life is.

All you can learn from failure is to avoid that particular kind of failure. And so what? There are too many other kinds of failure for that to make any difference. You need to learn from success. You should be spending your time trying to learn from success.

The successful entrepreneurs I have known have had the ability to look at a failure, any failure, and pull out the couple of things that were done right. These are what they focused on. Think about the successful entrepreneurs you know or have read about. This is just true.

If you're going to learn from failure you need to learn how to avoid every possible way you can fail. It's a waste of your time. You only need to learn one way to succeed.

Making Everyone a Data Scientist

noreply@blogger.com (Jerry Neumann) — Fri, 26 Apr 2013 20:34:00 +0000

You probably won't believe this.

There was a time when putting up a decent web page was considered a highly technical skill. In the period 1996-2000 most companies, even most big companies, had homepage designs that were raw HTML: static, poor design, broken links, nowhere to go and nothing to do. People had a name for it, brochureware, that was how common it was.

Firms like Razorfish and Red Sky specialized in using bleeding-edge technologies like CSS and DHTML to build sites that represented brands and told a story, that interacted. They hired the best coders and designers to do it, because it wasn't easy building a web site. The established agencies and design firms could not compete because they could not find enough people to hire who could build a competent site.

Crazy, right? Now ten year olds build web sites. College students put together calling-card websites overnight that rival what would have taken months and a team of people fifteen years ago.

That's how technology works. From magic to art to science to taken for granted. There was a time every car driver in America knew how their car engine worked; they had to. There was a time every programmer knew some machine language. There was a time everybody in the Internet business could tell you about what protocols they used in every layer of the OSI stack. One day every practitioner needs to know some technology. The next day it is invisible. We move up a conceptual layer and the layer below can be safely ignored.

Donald Norman, in The Invisible Computer, says

Everything changes when products mature. The customers change, and they want different things from the product. Convenience and user experience dominate over technological superiority. The company must change: it must learn to make products for their customers, to let the technology be subservient... The normal consumers, who make up the bulk of the market, consist of people who just want to get on with life, people who think technology should be invisible, hidden behind the scenes, providing its benefits without pain, anguish and stress... If the information technology is to serve the average consumer, the technology companies need to... start examining what consumers actually do. They have to be market driven, task-driven, driven by the real activities of those who use their devices.

Or, here's designer Jack Schulze, quoted in Domus:

Tech won't be visible but only if it's embedded into the culture that it exists within. By foregrounding the culture, you background the technology. It's the difference between grinding your way through menus on an old Nokia, trying to do something very simple, and inhabiting the bright bouncy bubbly universe of iOS. The technology is there, of course, but it's effectively invisible as the culture is foregrounded.

Does that tell you when? As an investor, I'm deeply interested in when. There are times I look at a particular sub-industry and it seems to be spinning its wheels. That usually says to me that the best place to innovate is actually a layer down in the stack. And there are times when I see awesome technology that is bottlenecked by a shortage of people who understand it. That's when it's time to move up a layer.

This second could be restated as: when a technology becomes too sophisticated for its users to use, make it a platform and build a user interface layer on top of it. That this makes sense seems obvious, how to do it is not.

*****

I invest in data businesses. Messy, technical data businesses. These companies deal with enormous amounts of real-time data. They push Big Data technologies, machine learning, and data visualization to its limits. They are always and constantly in search of people who can make these technologies work, and they're hard to find. Time to move up the stack.

I became involved with several companies in the data science industry: Metamarkets and Ufora in big data, Granify and BigML in machine learning, and Datadog, Lucky Sort and DataHero in data visualization.

DataHero just released their product this week. I think it's a great example of user-centric design, of de-magicking the tech.

I am as good as it gets when it comes to Excel. I was a consultant and a financial analyst for years when I was younger. But even so, when I pulled some AIPP data a few weeks ago to analyze it, making reasonable charts still took me an hour. Cleaning the data, organizing it the right way, deciding which charts would actually show anything, making the charts, and then exporting them so I could put them on the blog. Time suck.

Here's what I did with DataHero.

Connected to my Dropbox, downloaded the dataset I had stored there as an Excel file, made sure Datahero had guessed the datatype in each column correctly (2 minutes);
Dragged and dropped the x and y-axis variables onto a new chart, filtered out bogus values, tried different chart types (2 minutes per chart);
Exported the charts (like 10 seconds each.)

Here are the first two charts from the AIPP blog post. Total elapsed time: 5 minutes. Compare that to the original hour

Those two were fast because I already knew what I wanted. I then spent another fifteen minutes screwing around, tried about ten different charts to find three I thought had some explanatory value.

The obvious difference between doing this in DataHero and doing it in Excel was speed and bypassing the boring cleaning, categorizing, moving columns around, trying to figure out why Excel doesn't understand what I'm trying to do. But the less obvious and more powerful difference is that DataHero foregrounded what I was trying to do as a user.

The reason data visualization is such a powerful tool is that we, as humans, are better able to understand images than numbers. Tufte says, in closing his landmark The Visual Display of Quantitative Information,

What is to be sought in designs for the display of information is the clear portrayal of complexity. Not the complication of the simple; rather the task of the designer is to give visual access to the subtle and the difficult--that is, the revelation of the complex.

But this then begs the question: how do I figure out how to display the complex when it's so damned complicated? The AIPP data I was working with had no clear patterns at first glance, the set was too big for that. There are algorithmic techniques to discover order in large sets of data and there are simple hypotheses that can be confirmed or not. But doing either of these takes a decent amount of expertise and time. This sort of revelation requires the priesthood's guidance.

The third technique is more quintessentially human: tinkering and visual discovery. But this is not feasible for the non-programmer: it takes too long for each chart and making even small changes to the data being used is almost like starting all over. By taking away the complexity with automation and a user-centric interface, DataHero makes it possible to make as many charts as you like and throw away all but the ones that "give visual access to the subtle and the difficult."

The idea is to give everyone the ability to do most of what data scientists do today. Back in the '90s there were only a few really interesting websites because there were only a few people who could build interesting websites. Today there are only a few really interesting data visualizations because there are only a few people who can make really interesting data visualizations. When anybody and everybody can make sense of the complex data we're surrounded by, what will they find?

In all of the data science technologies, it is time for user-centric tools, tools designed around the real activities of their users, tools that foreground the culture. Because when the tool becomes invisible enough to us we can start to focus on what to do, not how to do it. That's where we can start to create real value.

Andy Weissman on entrepreneurship, product development and the future of the Internet

noreply@blogger.com (Jerry Neumann) — Thu, 25 Apr 2013 12:03:00 +0000

Andy Weissman is a partner at Union Square Ventures and one of my favorite people in the startup world. He was a co-founder of Betaworks and was previously at Dawntreader and AOL. His easygoingness belies the fact that he's one of the most thoughtful investors in the business.

Andy came up to talk to my entrepreneurship class at Columbia University's engineering school. I have people from the startup world in class every week. The point is not to have them teach, but to have a conversation with the class about what it's like to be an entrepreneur and to be part of the innovation economy. If the three turnings of the wheel are learning, knowing, and enlightenment, the speakers bring about the second: not what we do in the innovation economy, but what we are. Andy's talk is a great example.

Andy talks about what an entrepreneurial environment looks like--even in a company that's no longer a startup, how Betaworks did product development, where he sees business on the internet going, and what USV looks for in a startup. Andy's a really approachable and engaging speaker and I wish I could have had him talk twice as long.

Some marks:
0:00 - Intro, Andy's early career, at AOL
7:17 - Starting Betaworks
11:52 - Joining Union Square Ventures
13:47 - AOL diaspora
14:49 - Background of entrepreneurs
19:14 - Entrepreneurial environments--autonomy and empowerment
21:34 - Life after an acquisition
22:30 - Ideation and product development at Betaworks
30:55 - Evolution of internet business
33:20 - Next stage in internet business evolution
40:21 - NYC's internet ecosystem
44:39 - Is there a 'New Tool' now?
45:56 - Future of the internet
48:16 - What is USV looking for in a startup?
53:06 - Balancing data and gut feel in evaluating your startup idea
55:54 - Regrets?
56:32 - Most intriguing company he hasn't invested in.

If my fourteen-year old got her hands on this video it would have jump cuts and pan zooms and a swelling soundtrack and lots of duck-faces. Instead you get what you get: occasional bursts of static and a weird pan to the previous class' blackboard notes. And no, I have no idea what those equations mean.

A Tool for Open VC Data

noreply@blogger.com (Jerry Neumann) — Mon, 15 Apr 2013 13:03:00 +0000

A week ago I posted an idea for VCs to share their investments in machine readable form from their own websites. This is the simplest possible way to open up that data without relying on an intermediary that might either become a middleman or a bottleneck.

The first pushback on the idea was that VCs valued being obscure and so wouldn't cooperate. I wrote something in Forbes yesterday in response. The subtext is that some VCs won't share data but there's nothing you can really do about it except recognize that the ones who do share are probably better partners for entrepreneurs.

The other criticism came from Greg Yardley who emailed me to tell me that the sample investments file I put up had a syntax error. I had missed a bracket. Javascript is fiddly. To help me out he put up a tool with a user-friendly front end to create the portfolio objects. This should help you out too if you're going to put one up on your site.

He also improved the spec. He renamed the file from portfolio.js to investments.js--a more accurate description--and added things to the spec that real computer people have, like a version number. The new spec is here.

The tool is at VCDelta.org. It does several things:

You can create a new investments.js file. This also has the very cool feature of being able to import your existing Crunchbase data to use as a starting point. Huge time saver.
You can edit an existing investments.js file, the site copies the data from your website.

In both cases the result is a investments.js object. You need to copy this onto your computer and upload it to your website.

Copy-paste it using a text editor or some-such,
Save it on your computer as "investments.js",
Upload it to your site using an FTP client, then
Let me know! Email me, tweet me (@ganeumann), tweet to @VCdelta, comment on this post or whatever and I will put you on the list of known investments.js files.

Note well: The site does not save your investments.js file, you need to do this yourself. If you leave the site without creating a js object and copy-pasting it to your own machine, you will lose your work. The whole idea is to have us all own our own data. So own it.

Thank you Greg!

A Mechanism for VC Deal Transparency

noreply@blogger.com (Jerry Neumann) — Mon, 08 Apr 2013 13:46:00 +0000

[Edit: Greg Yardley has built a tool to implement this. I talk about it here.]

There was a bit of a brou-ha-ha last Friday over VCs not publicizing their investments. I was dubious: I've never met a VC who didn't want the world to know about every investment they make. It's a crowded market and letting entrepreneurs know you're making investments lets them know, well, that you're making investments. All of us investors need to let the world know we continue to exist because if we don't, we soon cease to exist. Publicity around deals is by far the easiest way to do that.

But over the past few days I was challenged by entrepreneurs to provide more information. "Through what mechanism?" I asked. There was no good answer. Crunchbase, great for what it is, is not a good mechanism. Perhaps the entrepreneurs don't realize this (or perhaps I'm doing it wrong) but even though CB is wiki-like, I can't edit the "Investments" section of my page; I think only CB admins can. Because I'm never sure what the process is, I have neglected it. But there should be a mechanism to update our portfolios and it needs to be Internet-y: simple, end-to-end, machine readable.

In some sense, this already exists. It is the VC firm portfolio pages. That's why I built @VCdelta two years ago, to disseminate information that VCs are making public on their sites. It's been pretty successful. It's followed by many VCs, entrepreneurs, and journalists. And when I've had trouble scraping VC sites--because VCdelta is indeed a scraper--VCs have usually helped out. The reason I've needed their help is because VCdelta is a good citizen, it doesn't scrape sites that don't want to be scraped. It doesn't hide what it is--a python client--and it obeys robots.txt. Some sites were accidentally set up with defaults that exclude it.

It's okay if a VC does not want to share information. Those that share information get more attention, more love from entrepreneurs, and better deal flow. At least that's what I believe. And I've had many VCs bring themselves to my attention so they can be added to VCdelta's scrape. I do what I can.

But here's the rub: I don't like being a bottleneck. I'm providing a service and it's automated so it doesn't take much time*. But being a scraper, it breaks. And then some firms decide to use technologies that are more viewer friendly that VCdelta is not set up to handle, like AJAX or Flash. Some firms use images on their portfolio page that have no company name associated with them. I don't have time to make it better. And, in my own opinion, it pretty well sucks right now. Firms like Intel Capital have never been included. First Round Capital broke after they moved to an AJAX portfolio page. Etc. These are important firms, and I don't have time to get them back into the program.

So I have a proposal. If investors want to publicize their deals in a usable way while not relying on a third-party gate-keeper, then we need some common language and setup to communicate. It should be simple, hosted on the VC website, and machine readable. Something like this, my investments**.

It's a Javascript object. It's machine readable. E.g. in python:

import urllib2, simplejson as json
portfolio = json.loads(urllib2.urlopen("http://neuvc.com/investments.js").read())

The object is formatted like this:

[{"company":"companyname1",
 "url": "http://www.companyurl1.com",
 "rounds":[ {"Series": "Seed", "date":"06/2009"},
   {"Series": "A", "date":"04/2010"}, ...]},
{"company":"companyname2",
 "rounds":[ {"Series": "Seed", "date":"08/2008"}, ...], 
 "events":[ {"event":"Sale to BigCo", "date":"10/2012"}, ...]},...]

My proposal is that investors put this type of file up on their homepage and keep it updated. If we roughly agree on a format and location third-parties can easily find out what we are doing. This is not my standard, it is a proposal for a community standard. I disclaim any ownership of it. If someone wants to publish a similar format for funds raised and fund personnel, please do. I'm a one-person, bootstrapped operation so don't feel my opinion is of much weight for those.

If you decide to use it, let me know. I will have @VCdelta tweet any firms that adopt it.

You may or may not believe that investors are being transparent enough, but some of our customers believe we are not. This is a mechanism to address that, if enough people choose to adopt it.

-----
* Normally I would publish the code, but it was built accretively so it's spaghetti and I'm embarrassed to have anyone else see it. I have had on my list to rebuild it from the ground up, but it's been on my list for 18 months.
** There is one investment not on the list because the entrepreneur has asked me not to disclose yet. The wishes of my entrepreneurs trump your need to know. Sorry.

The Signal and the Noise (Angel Investing 6)

noreply@blogger.com (Jerry Neumann) — Thu, 04 Apr 2013 13:07:00 +0000

[Note: Post Number 5, on modelling your portfolio, was supposed to be next. Then I asked my friend Chris Wiggins a naive question about power law distributions. In return he sent me this paper. And this software. And this syllabus. And this paper. And this video. And also this talk he gave, which was above my pay-grade. And then I read the papers and watched the video and I was enlightened. And then I ran the software and it told me that the returns in the AIPP data were not power law distributed, that it was far more likely they were log-normal distributed. And I knew there would be a whole 'nother set of papers and videos and online coursework. And so I threw up my hands and wrote this post instead. I'll get back to the other one when my brain recovers.]

A long-time VC at a top tier firm said to me the other day: "we used to talk about proprietary deal flow, but that doesn't exist anymore. Good ideas can get in front of anyone and good founders make sure they do." Mahendra Ramsinghani* makes the same point yesterday on PEHub. It's true.

There was a time, say three years ago, when you could see great deals that no one else saw. That time is gone. Great deals are seen by plenty of people. Anyone can easily invest alongside me, or David Lee of SV Angel, or Founder's Fund, or almost any other great investor.

But this does not mean that you will automatically see great deals. Deals don't just suddenly start landing on your desk the day you decide to start investing. You need to make yourself known, then you need to make yourself wanted, then you need to make yourself needed. That takes some work.

And then, as soon as you start generating signal, you have to deal with the noise.

As an investor you will see a lot of potential investments for each one you make. Venture capitalists say they see 100 plans for every company they fund. There are a few reasons for this:

Most businesses should be friends-and-family funded, or bootstrapped**, not venture funded;
Most startups that should be funded should not be funded by you; you should invest in what you know: the people, the market, the types of activities the firm will need to excel at to thrive;
You may see several companies solving the same problem at the same time, but you probably don't want to have too much bet on a single problem;
Related, you will need to say no to good companies because they are too similar to companies you've already invested in;
You won't know which are the best new companies unless you are seeing a lot of them***, you won't know where the market is pricing companies if you aren't talking to a bunch of them, you won't know what problems companies in that industry are facing, you won't know which other investors are actively in the market, etc.

You want to see many of the deals you end up not investing in. Venture investors traffic in information. Good venture investors are great information processors. Looking at companies is the best source of information out there. But a lot of deal flow is unavoidably noise to you, not signal. Although I would be interested to know more about the wave of online consumer subscription retail startups, for instance, they are too tangential to my main investment theses for me to spend the time meeting with them all. I need to just say no and move on.

Once you open the door to any and all deals, you're drinking from a firehose. You can't look at everything. You need a mechanism to filter for the deals that fit your criteria, and you need to do it in a time-effective way. That may be the harder part of deal flow: not quantity, and not quality exactly, but finding the needle in the haystack.

Ramsinghani correctly chides the VCs he's invested in to no longer consider proprietary deal flow a competitive advantage. But I don't think it means what he thinks it means. VC investing has become democratized. But the result is not that everyone now has the same advantages, it means that everyone now has the same problems. Established VCs have processes to separate the signal from the noise. You need them too.

Next: Generating deal flow

Previous posts in this series

Intro: Why I'm Not an Angel
How to spend your time: The Work-Work Balance
Positioning: How to be Different When What you Sell is a Commodity
Portfolio Construction: Transcending Hobbyism

Data sidebar: AIPP data summary
Data sidebar: AIPP exit data

Portfolio Modelling: TBA

-----
* Who, btw, wrote the book on venture capital as a profession: The Business of Venture Capital
** For many reasons--the return needed to compensate for the risk around a raw startup, the need to get to a cash exit (not just a sustainable business), the principal-agent risk, etc.--most startups should be self-funded or backed by friends and family or supported by the founders starting the company on the side. The National Venture Capital Association says that in 2011, only 973 startups received their initial venture capital funding. CB Insights has said closer to 2000. In comparison, the Bureau of Labor Statistics says that in March 2011, there were 536,445 establishments less than a year old. These numbers are not apples-to-apples, but the point is that far fewer than 1% of new businesses take venture money.
*** Saying this may rub some entrepreneurs the wrong way, they don't want their time wasted responding to fishing expeditions. I agree. Do not waste entrepreneurs' time. Be honest. As soon as I decide I'm not investing, I tell the entrepreneur. If that's before the pitch I also often tell them that I would be happy to sit down and hear their pitch anyway. Many times they take me up on it. In return, I try to be helpful: constructively critiquing their plan, offering to make intros to portfolio companies or other potential partners, etc. My existing portfolio companies always come first, but in almost all cases in the startup world, the competition is not other startups, but established companies. I like helping startups, and if I can help without disadvantaging the companies I've already made a commitment to, I will.

AIPP Data Modeling (Angel Investing, Sidebar 2)

noreply@blogger.com (Jerry Neumann) — Mon, 01 Apr 2013 19:14:00 +0000

More from the Angel Investor Performance Project data.

Much of the financial activity at early stage companies happens around investment rounds. Acquisitions, failures, and fire-sales tend to happen when it's time for the company to raise more money. So it doesn't make sense to look at rates of failure or exits divorced from the fund-raising process.

Here's a look at the AIPP data from the last post. Company exits and the sale multiples by years held. A zero multiple means the company failed.

	Sale Multiple
Year	0	0-1	1-2	2-4	4-8	8-16	16-32	32-64	64-128	128-256	256-512	>512
0	5	3	0	1	0	0	0	0	0	1	0	0
1	22	8	3	35	1	2	1	0	0	0	0	0
2	36	24	6	5	3	1	1	1	0	0	0	0
3	25	6	6	8	21	1	1	1	1	0	0	0
4	29	8	3	39	1	1	1	1	0	0	0	0
5	14	23	7	6	1	0	0	0	0	0	1	0
6	2	2	1	1	1	1	1	2	0	0	0	1
7	1	5	6	0	0	1	0	0	0	0	0	0
8	1	2	1	1	2	1	0	2	0	0	0	0
9	0	0	0	0	0	2	0	0	0	0	0	1
10	1	0	1	0	0	0	0	0	0	0	0	0
>10	11	0	0	0	2	1	1	1	0	0	0	1

Note the oddly large numbers in the 0-1 multiple range in years 2 and 5. My hypothesis is that these were companies that could not raise their next round (the A and the B, I assume) and went through a fire-sale, resulting in some money to the investors but not a gain.

What would Markov do?

This, I think, more closely corresponds to reality than the continuous assumptions most analyses take. Note that this roughly agrees with the common wisdom that 1/3 of venture-backed companies fail (here, 34% overall), 1/3 return capital (here, 19% overall are fire-sales so return >0x and <1x, but some bleed-over into slightly more than 1x returns could be attributed to the 1/3 "return capital") and the rest make money for the fund.

The AIPP dataset is not large enough to be able to make good predictions about sale multiples at each round. But if we assume that

Venture investments as a whole make 25% p.a.;
Venture funds end up returning 2x cash on cash on average;
Seed is in year 0, any A would be in year 1, any B would be in year 3; and
A sale after the B would be in year 6.

Then we can model the multiples at each point. The mean cash-on-cash sale multiple would be*

Full follow-on:

1.6 for pre-A sales,
4.4 for pre-B sales, and
4.7 for post-B sales;

No follow-on**:

1.6 for pre-A sales,
6.4 for pre-B sales, and
10.2 for post-B sales.

Actual multiples would follow a power law probability distribution, as noted in the first sidebar, with these as the means.

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* I doubt this is a unique result. In configuring the model behind these this seemed most reasonable to me given my experience.
** If you follow on, then you invest money in the A and B at a higher valuation, so your eventual multiple is lower, albeit on a larger investment.

AIPP Data Summary (Angel Investing, Sidebar 1)

noreply@blogger.com (Jerry Neumann) — Sat, 30 Mar 2013 20:24:00 +0000

The Kauffman Foundation has some data on angel investor investment and returns at their Angel Investor Performance Project. The data has some serious limitations, mainly that it is relatively concentrated in time (44% of the investments with data are '99 or '00), that there's not enough investments to draw fine-grained conclusions, and that valuations at each investment are not available so follow-ons are hard to interpret. That said, data is better than no data. A summary below*.

		Multiple
		0x	0x-1x	>1x	All
No follow-on
	Total companies (% of all)	97 (66%)	50 (61%)	158 (81%)	305 (72%)
	Average exit multiple	--	0.47	28.27	14.72
	Average years invested	2.9	2.8	3.6	3.2
	Average invested	$88,420	$109,678	$90,125	$92,788

Follow-on
	Total companies (% of all)	50 (34%)	32 (39%)	37 (19%)	119 (28%)
	Average exit multiple	--	0.33	7.00	2.27
	Average years invested	2.8	4.5	4.9	3.9
	Average invested
	Initial	$346,460	$86,836	$129,730	$209,259
	First follow-on (% of initial/% of companies)	$194,345 (56%/100%)	$41,946 (48%/100%)	$92,524 (71%/100%)	$121,705 (58%/100%)
	Second follow-on (% of initial/% of companies)	$66.080 (19%/20%)	$17,425 (20%/13%)	$13,097 (10%/8%)	$36,523 (17%/14%)
	Later follow-ons (% of initial/% of companies)	$19,600 (6%/10%)	$5,625 (6%/13%)	-- (0%/0%)	$9,748 (5%/8%)
	Total invested (% of initial)	$626,485 (181%)	$151,831 (175%)	$235,350 (181%)	$377,234 (180%)

All
	Total companies	147	82	195	424
	Average exit multiple	--	0.42	24.23	11.23
	Average years invested	2.9	3.5	3.9	3.4
	Average invested
	Initial	$176,189	$100,764	$97,640	$125,477
	Follow-ons (% of initial/% of companies)	$95,247 (54%)	$25,364 (25%)	$20,041 (21%)	$47,144 (38%)
	Total invested (% of initial)	$271,435	$126,128	$117,681	$172,621

Some thoughts. The data is noisy and there are outliers that skew it. This shouldn't surprise anyone. I would have expected that the deals with follow-ons would have returned more absolute dollars than those without, albeit at a lower multiple. The lower multiple is there, but the total average dollars returned is about a third. This means one of two things: 1) angel investors primarily invest in follow-ons when the company sucks, or 2) there is not enough data to smooth out the statistical anomalies. I think the second is probably truer. But there is also some truth in the idea that angel investors may not get a chance to invest in later rounds when the company is going gangbusters. The deals with follow-ons also exit later, even the successful ones, so some companies may not have angel investor follow-on because they exit before another round is needed.

Failure rates are pretty high. About a third of the companies fail outright. Another 19% don't return capital. The remaining 46% pay out. Here's a graph of exit multiple vs. years invested.

I cut off one or two multiples above this range and a couple of exits that were more than 14 years out so you could see the structure. I would describe this as consisting of two things overlaid (although I don't think there's enough data to prove it): 1) a group of investments that follow a constrained exit pattern--this is the bulk of the exits, peaking at three years and then declining until it disappears at eight years--and 2) investments that don't seem to follow a particular pattern. This jibes with my gut that says some investments are 'earners', they are less risky but have less upside. These companies build then exit. Other investments are the 'swing for the fences' types. These can exit anytime and for any amount.

Here's a chart of how long the angel investors held their investment before exiting.

And here's a chart of exit multiples.

This is a log-log chart, showing that even with this noisy data, exit multiples follow a power law.

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* I cleaned the data. I removed any deals that: did not have exits, did not have a number greater than zero in the 'totalinvested' column, and any where the 'stage' field was not either blank, seed, or startup.

Transcending Hobbyism (Angel Investing 4)

noreply@blogger.com (Jerry Neumann) — Wed, 27 Mar 2013 13:30:00 +0000

A company I really liked was out raising money. They went to a very well known early stage VC and had a great first meeting. A couple of days later the partner got back to them with a no. He said "We really like you and your company, but we have a portfolio construction problem." The entrepreneur called me. "What the hell," he asked, "does that mean?"

As an investor you don't just pick the good ones and walk away from the bad ones. Were it so easy. You are managing a finite pool of money and are looking for the best return on the pool, not just on each individual investment. That means that sometimes you have to walk away from a good one. The easiest way to separate the serious angel investors from the hobbyists is to ask them about their approach to building a portfolio. Serious angels have a plan for what they are trying to build. Hobbyists are just piling up stones.

Here are some questions. They're analogous to the questions you ask entrepreneurs when you're trying to figure out if they've thought their plan through: How much money do you need? What will your burn be? How long until you're profitable? Startup venture funds are not like the startup ventures they fund. But, like startups, they need to have a viable business model. And, like startups, that includes not running out of money halfway through.

First, how much money can you invest in startups?

I'm not going to give you advice on this because I'd be a hypocrite. I long ago blew through whatever reasonable percentage of my cash I should have put into this incredibly risky, close-to-zero liquidity asset class. Do what someone else says, not what I do. Most commenters say you should only invest what you are comfortable losing. That's solid advice*. Big institutional pools of capital often reserve 2-10% of their assets for private equity, of which venture capital is one fifth or less. I'll leave it at that.

Second, how many investments do you plan to make?; third, how much work do you plan to do with each company post-investment?; and fourth, will you have an investment thesis?

We all know it's the right thing to do to invest in a portfolio of companies to avoid idiosyncratic risk--the kind of risk that is specific to a single investment. If you have a large enough portfolio--common wisdom is some 20-25 companies--of uncorrelated investments then you have pretty much minimized the unsystematic risk.

Related is the idea that since venture investing is a hit-based business, you need to have a lot of investments to have a good chance that one is a hit and returns your entire pool of capital several times over***. The number of investments to make it probable for this to happen has been estimated at between 20 and 150.

These numbers don't take a few things into account, and you should.

Getting rid of diversifiable risk makes sense: the risk that a portfolio CTO quits after six months, that Google unexpectedly launches the exact same product, that your platform decides to ban the way you make money. Sometimes you should know this is going to happen before you invest (I'll talk about due diligence in another post) but sometimes there's no way to know. Having many companies means that if a couple hit one of these deadends, you're not finished. But keep in mind that diversifiable risk presupposes a lack of correlation between investments. The risk that a CTO leaves one company is uncorrelated with the risk that the CTO of another company also leaves. On the other end of the spectrum, the risk that there's a financial crisis and every venture investor simultaneously decides to stop doing Series As is 100% correlated across all seed-stage companies: it's a market risk and you can't get rid of it through diversification.

But in the middle are the the kind of semi-correlated risks that are the bread and butter of every good venture investor, the risks that go with a particular sub-industry. The risk of Netscape changing third party cookie policy from opt-out to opt-in is correlated across most ad-tech companies but not many other internet companies. There are similar risks to any investor's thesis, be it Big Data, Social, Consumer Internet, whatever. But trying to entirely diversify away these risks means you can't really have any thesis at all. And that means you can't have any expertise. The market risk in finance is called β and is the best you can do in an efficient market--one where all information is available to all participants. But if you feel like you know something that not everyone knows, that you're an expert at something, then you can generate α, return in excess of risk taken. β is what asset allocators brag about. α is what investors brag about. We like α.

There are two strategies: create an index-fund like portfolio with 100+ relatively uncorrelated investments and try to get β, or create a 20+ portfolio of companies you actually know something about--less diversification but more α. The latter strategy is riskier: if what you believe about the market turns out to be untrue, that whole part of the portfolio goes bad. But if it's right, you do better than the market.

There's also, of course, an impact on how much money you spend and how you spend your time. Many founders don't want investors who are putting less than $25k or $50k into the company. You may find that you don't have enough money to get to a fully-diversified portfolio. You should think about this carefully. If you're not somewhat diversified, you are handicapping yourself relative to other investors and you face a pretty decent probability of actually losing all your money****.

And then there's how you spend your time. If you hope to help the companies you invest in grow by being active, you can't make 100 investments every few years unless you have some infrastructure to help you.

Fifth, what stage will you invest at?; sixth, swing for the fences or go for earners?

I assume that most angels invest at the seed stage. It's the only time when you can get an appreciable piece of the company for an angel-sized stake. But there's seed and there's seed. If you put in first money like I try to do, when it's two people and a pony, you're taking more risk and will need to hold the investment longer before exit. But you get to invest in the best people and the best ideas. If you invest after there's a minimum viable product and the company is looking for some money to start getting customers, then you have less risk--you can assess the strength of the team as a team and look at the MVP as a product and talk to potential customers about how burning their need for it is--but by then you're probably competing with many other investors to get a piece of the deal.

In my experience, if you invest at the very start of a company, you will end up holding that investment for some six to eight years. Some companies exit sooner (although it's rare for one to exit less than three years after inception) and some take longer (I was recently talking to the founder of a company I invested in thirteen years ago--and it was two years old when I invested--about starting to look for a buyer.) In any case, you should expect a substantial period of illiquidity.

The type of company you're investing in also makes a difference to holding period. The companies that are swinging for the fences usually take longer to mature. Simple, for instance, whose vision is to disrupt retail banking--one of the largest industries in the world--by actually treating their customers like customers took three years from idea to launch. Less ambitious companies can start, launch a product, and sell in less time.

Some investors prefer the less ambitious companies, the earners, hoping to build and flip in a short period of time. I don't. I tend to follow the old adage of shooting for the moon and landing on the roof. If you're trying to build a billion dollar company and fail, you might end up with a $50 million exit. If you're trying to build $10 million company and fail, you end up with nothing. But that's personal style; there are prominent counterexamples.

Seventh, will you follow on?

Related is whether you follow-on or not. That is, having invested in the seed round, do you also invest in future rounds?***** I'll talk about whether this is a good idea or not in a later post, but if you decide you want to be able to follow on, you need to reserve money for it.

In my portfolio, the average amount raised has been about

First round	$1.3 million
Second round	$4.7 million
Third round	$7.7 million

If you invested $50,000 in the first round at a $5 million post-money you would own 1%. Then you could expect that your pro-rata of the second round would be $47,000. Your pro-rata of the third round would be $77,000. Your $50,000 is now close to $180,000. I usually stop investing after the B. I reserve twice my original investment for follow-ons, assuming that some companies won't raise the A or the B.

Putting it Together

I ask my founders to build a financial model, even though it's inevitably wrong--"prediction is hard, especially about the future." But the act of building it means they need to think through tradeoffs, milestones, capital needed, etc. While the decisions they make because of this thought experiment should evolve as actual facts come in, the exercise of modeling allows them to know what their envelope of viability is. Answering the above questions should allow you to do the same.

NB: The undisputed master explainer of these types of issues is Roger Ehrenberg on his Information Arbitrage blog. His post on Portfolio Construction goes way more into depth than I have. Also read at least The Right Fund for the Mission.

Next: Modeling your fund [edit: not done yet, skip to The Signal and the Noise for now.]

Previous posts in this series

Intro: Why I'm Not an Angel
How to spend your time: The Work-Work Balance
Positioning: How to be Different When What you Sell is a Commodity

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* Long ago a girlfriend brought me to a gathering of her friends. We joined a couple of other couples playing penny-ante poker. After I goaded the others into betting BIG (literally HUNDREDS of pennies) the gf walked away from the game. She chided me afterward: "Why were you being such a dick? We were just trying to have fun." I didn't get it. If it isn't painful when you lose, why even play?**

** Also, why I don't blog relationship advice.

*** The difference here is a bit confusing. Diversifying away unsystematic risk means that you actually increase the expected value of your portfolio for any given amount of risk. Making lots of bets in a hits-based business doesn't increase your expected value, it decreases the variability of your outcome.

Think about it this way. There are ten upside-down bowls. Under one of them is a $20 bill. You can 'buy' any bowl for $1. Since each bowl has a one in ten chance of having $20, your expected value of each bowl is $2. The smart thing to do is to buy all the bowls, spending $10 to get $20. Your expected value does not change (it's still 2:1), but the variability of your outcome has gone to zero: you always get the payout.

Of course, if you bet on a single bowl and won, you'd get a 20:1 payout. It's because you know nothing about the bowls that you're better off buying them all. If you have an inkling about which bowl is more likely to have the money under it then you're better off just buying that one. The idea that you should make 150 investments to lock in the average angel investing return presupposes that you have no idea which companies are better than the others. I've never met an investor who truly believed this. I consider myself pretty damn humbled by experience, but even I'm not that humble.

**** The astute reader will observe that if you follow the rule from question 1 and only invest what you're comfortable losing, you may put yourself in a position where you're more likely to lose it. You then have the choice of one of two mantras: 1) "The rich get richer, not me", or 2) "I am large, I contain multitudes."

***** If you decide you want to be able to follow-on, you need to negotiate pro-rata rights into your deal. I'll talk about this and other deal terms in a later post.

How to be Different When What you Sell is a Commodity (Angel Investing 3)

noreply@blogger.com (Jerry Neumann) — Mon, 25 Mar 2013 14:40:00 +0000

When I started a company my co-founders and I thought and discussed and argued about how we were different from our competitors, how there was a hole in the market, how we were going to win by going where no one had gone before. We got potential customers, suppliers, employees excited by talking about how we were different.

If an entrepreneur were to map venture funds on a traditional 2x2 competitive matrix, using their two most important value propositions as the axes, it would look like this*:

In the things entrepreneurs care about most--price and control--VCs don't seem all that different from each other. That's not going to change and you're not going to change it. Venture capital is already a business which is, at best, on the edge of being uneconomic**. In the times when VCs have been sucked as a group into competing on price, the whole sector has done badly.

In the product world, if you are really good at something, you compete on price to take more market share. In the services world, where your expertise isn't that scalable, when you're really good at something you raise your price. VC is a service business and I often see the VCs with the best reputations offering a deal that is slightly worse than average and still being chosen as the funder. Conversely, I have often seen lesser known VCs or financial backers from outside the VC world offering much richer deals in order to be chosen. If you want to have price discipline (and you do) then you need to offer something besides price, and it better be good.

Ask yourself: how do I distinguish myself from all the other sources of money out there?

This seems like a ridiculous question to some. You, after all, have the money; shouldn't you be the one doing the distinguishment? When you walk into Tiffanys with a Hefty bag stuffed full of large bills, the salesman doesn't ask "Why should I do business with you?" He sprints across the floor and asks "How can I help you?" Thinking this is how it works in angel investing is a classic rookie mistake. The founder who is willing to take your money regardless of anything else you bring to the table is the founder who can't get money from anyone else. This means one of two things:

You are smarter than all of the other investors and see something they don't, or
The company is not a great bet.

The first situation happens. I've done a few of those, as has any venture investor worth their salt. But the majority of great investees are good enough bets to have many interested investors. If you want to be in these you need to offer more than just money.

There are many ways to add real value through the process. I'll talk about that in detail in a few posts. For now you need to think about positioning in general, about what you have to offer, both so you can generate the right kind of deal flow and so you can plan your investing strategy.

Here's a potentially scurrilous example of positioning among early-stage VCs.

Each of these funds has been very successful at being chosen by great companies to be their lead investor and they've each staked out different investing strategies. The x-axis is the amount of team, product and market risk they are willing to take (less to more as you move right.) The y-axis is how much operational help they offer, from incubator or incubator-like at the bottom to hands off at the top. The z-axis is how deeply they know a specific industry or technology***.

In reality, none of these funds fits as well into their box as this graphic makes it look. And each offers something that this box doesn't capture (not least, among this group, attitude.) But you should have a sweet spot, you should be able to articulate it, and, more importantly, it should articulate itself through your actions and communication. Entrepreneurs will find you if they know you are what they are looking for.

Anywhere you choose in this cube has its tradeoffs. If you spend more time helping your entrepreneurs you have less time for other things. If you spend less time helping you are less valuable (assuming your help is valuable.) If you take less risk you either aim for lower returns or you face much more competition for investing in the deals. If you're more specialized you need to work harder on finding potential investees but you are better able to evaluate the ones you do see.

Where you fit depends on what you know, how much time you have and your personality. It will determine how you spend your time, how you generate dealflow, how you filter deals, and how much you can help.

Next: ~~Investing Strategy~~ Portfolio Construction

Previous posts in this series

Intro: Why I'm Not an Angel
How to spend your time: The Work-Work Balance

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* For the VCs' real customers, the LPs, it probably looks more like this.

** In terms of risk-return.

*** The risk-return profile, all else being equal, gets better as you move from bottom right to top left. That's why most funds are in the top left box. Of course, If all else is equal, maybe you should go find some other business where you do have an unfair advantage.

The Work-Work Balance (Angel Investing, 2)

noreply@blogger.com (Jerry Neumann) — Thu, 21 Mar 2013 13:28:00 +0000

The first question every prospective angel (and all my relatives) ask me is "What do you do all day?"

It's sort of a funny question. For any job more varied than working on an assembly line, the answer is either going to be pretty long or pretty vague. Usually I go with vague. Today I'm going with long.

Venture capitalists

Find companies that need capital,
Figure out whether they should invest,
Convince those companies they should take investment from them,
Negotiate terms, create syndicates of investors, and invest,
Help build the company,
Manage and protect their investment,
Manage and protect their portfolio, and
Exit--sell or shut down companies.

Institutional VCs also spend a good deal of their time getting investors for their own funds and then keeping them informed, but we're not institutional VCs, so we don't have to worry about that.

I have 23 companies currently in my portfolio. I invest in four or five new companies a year. I sit on five boards that each meet monthly or every other month, so one board meeting a week. I talk to another six company founders every week or every other week. I talk to an additional five company CEOs at least once a month. The others are further along and I talk to them once a quarter or so. On average each of my companies has a follow-on financing every 12 months so I evaluate a follow-on opportunity twice a month.

Given all that, here's how I spend my time:

Two days a week generating deal flow,
One day a week filtering deals that I see,
One day a week doing due diligence/negotiating terms/reading contracts/building syndicates on deals I like,
One day a week at or preparing for a board meeting,
One day a week talking to other portfolio founders/CEOs to see how they're doing,
One day a week looking at material/giving advice/making introductions for the other portfolio CEOs,
One day a week networking with other VCs/corporate types/other innovation professionals and answering random email,
One day a week keeping on top of industry developments and emerging technologies,
Half a day a week looking at follow-on opportunities,
Half a day a week making sure the i's are dotted and t's are crossed.

That's ten days a week. That's why I haven't answered your email.

Ok, maybe that's what I should do. Here's more like what I actually do:

One day a week trying to make sure people don't forget I exist: blogging, emailing people I haven't seen in a while, tweeting, coding stuff I think is interesting and putting it on the web,
A few hours a night trying to figure out what the hell is going on and trying to continue learning new things: reading everything I can get my hands on,
One day a week going to board meetings and talking to my other portfolio companies,
Half a day a week filtering the inbound deal flow,
One day a week looking at companies I think are especially interesting,
Half a day a week evaluating follow-ons, reading legal docs, keeping track of the portfolio as a whole,
One day a week meeting new people--entrepreneurs, people in the industries I'm interested in, other investors, random people friends say I should talk to, etc.,
One day a week prepping for, teaching, or doing follow-up for my course on entrepreneurship at Columbia.

That's six days. And that list is still a bit aspirational. I never get everything done. Tradeoffs.

Institutional VCs have to make tradeoffs too. For them a little bit of the stuff in the first list can be delegated (making sure the Is are dotted and Ts are crossed, some of the initial filtering of deals, some of the due diligence, a little bit of the helping portfolio companies.) And some of the stuff is made easier when you work in a team (filtering deals, evaluating follow-on opportunities, keeping on top of industry developments, networking.) But there's a reason most of the best VC firms--and all of the best early-stage VC firms--are partner-based, not hierarchical: almost all of these activities for any given investee or prospective investee need to take place inside the same brain if the process is going to be high function.

Angel investors don't have the advantage of delegating. And working in a team is usually pretty ad-hoc (unless you're part of an angel group, which then adds some overhead of its own) so trade-offs become more important. Angels (and super-angels and very small seed funds) choose different trade-offs. Some focus entirely on generating deal-flow but making sure someone else leads the deal: they do less evaluating and more networking. Some focus on adding a ton of value by knowing the industry they invest in extremely well: they do less deal generation (deals in their field show up on their doorstep) and more helping. But most fall somewhere in the middle.

I've made tradeoffs: I try to know the industries I invest in and so do more work on understanding specific sectors and a bit less work on generating deal-flow; I tend to invest as early as possible, so do more work trying to understand the founders and less work trying to understand what the company has done to date; I try to co-invest with people I trust so do more work talking to other investors and less negotiating terms and iterating legal docs; I'm an engineer so I spend more time building tools to do my work so I can spend less time doing the work; I'm not much of a schmoozer so I need to earn my keep by sitting on boards and helping founders. Luckily, this then cuts back on the time I need to spend networking.

Even so, it's pretty all-consuming. But if you hope to build a portfolio that gives you a reasonable chance of making money, all of the tasks in the first list are needed. How you spend your time getting those tasks done depends on your personality and your expertise. Figuring out what tradeoffs work for you is probably the most critical decision you can make.

*****

Next: ~~Positioning~~ How to be Different When What you Sell is a Commodity

Previous posts in this series

Intro: Why I'm Not an Angel

Why I'm Not an Angel

noreply@blogger.com (Jerry Neumann) — Wed, 20 Mar 2013 14:19:00 +0000

If you bootstrap your business it's your prerogative to make any stupid decisions you want--so long as you don't run out of money. But if you decide you want your bootstrapped business to be as successful as possible, you probably make pretty much the same decisions a businessperson backed by outside capital does. The process you use to grow a successful business does not materially change because of how you are funded.

So why do angel investors invest so differently than institutionally funded venture capitalists? Angel has come to be a bit of a pejorative, connoting a certain hobbyist nature, an unseriousness, amateurism. When entrepreneurs tell me they don't want venture firms in their seed rounds, just angels, my antennae go up: what are they afraid of, competence? I stopped calling myself an angel investor some time ago; I try to think about myself as a bootstrapped venture fund, doing the same job with the same professionalism on a smaller scale.

Every would-be angel I've met takes pride in their day job, they would never settle for stupid or unprofessional in their work. Even in their hobbies they would not be satisfied with sloppy or half-done. They are serious, successful people who have made their way by putting in the work to do their jobs right. So why, when they think about angel investing, do they impatiently jump right in with only half-assed attempts at learning how to do it right? Why do people who would never sit at a high-stakes poker table with hard-eyed strangers unless they had spent countless hours at lesser tables put tens of thousands of dollars into a startup without bothering to learn the rules, the odds, the other players?

Venture investing looks so easy from the outside. The public faces of VC--Fred Wilson, Mark Suster, Chris Dixon--are encouraging and open, willing to give pithy advice on the dos and don'ts. People like to talk about what they've done right and how more of that needs to be done. They don't tell the stories much about bad times, hard decision and all the work they did to create the few bright spots they write about. They like to make it look easy. If you read the VC blogs, you must wonder how they manage to fill their days when all they do is wander Union Square bumping into top-notch entrepreneurs, writing them checks on the spot, and then flipping the companies to Google or eBay for hundreds of millions of dollars. Union Square Ventures only invests in a handful of new companies each year--with five investing partners. Each partner only does a deal or two per year? It must be like a tropical vacation. Right?

In the New Yorker's recent portrait of Bruce Springsteen the author makes this distinction: "Keith Richards works at seeming not to give a shit. He makes you wonder if it is harder to play the riffs for 'Street Fighting Man' or to dangle a cigarette from his lips by a single thread of spit. Springsteen is the opposite. He is all about flagrant exertion." Many VCs are trying hard to be cool as Keith Richards. And hey, why not? If you can convince people that you invested in a billion dollar outcome by ignoring the dismissal of all of your peers and the common wisdom and instead just trusting your gut, or that you found the next big thing just walking the floor of a tech company occasionally glancing over engineers' shoulders at their screens, well that's probably about as cool as you can pretend to be if you're a financial intermediary.

But playing the guitar like Richards actually takes a ton of work and an enormous amount of repetitive practice, whether he acknowledges it or not. I'm here to tell you that Springsteen is being more honest than Richards: VC swagger is pure BS. Writing a check is easy; creating a decent chance of getting a bigger one back down the road is hard, damn hard.

Prospective angels ask my advice all the time, as one of the few people on the east coast who has made a living as an independent venture investor lo these many years. I'm happy to answer their questions, but I don't think any of them has ever taken any of my advice. Ben Franklin said "wise men don't need advice, fools won't take it." But I'm an optimist, so advice will follow.

This will be several posts, broken up into bite-size chunks. I will do my best to suppress my usual rambling ranting. Nothing I write in any of these posts is new. If you did your homework, all this would be old hat. That's part of the point: I'm going to lay out a score of pages to convince you that to be a successful venture investor you don't have to be a super-genius, you just have to actually do the work. The main take-away should be that there are no shortcuts.

Some caveats. I'm talking about a specific type of venture investing here, the kind I engage in. Investing in people that can use some modicum of cash to attempt to build a world-class company in a fairly brief period of time. I'm not talking about funding your cousin's restaurant or your buddy's bar. Those worthy endeavors have a different logic.

I'm also talking about aiming for a positive return on your investment. If your primary goal is to help out friends, give back to the community, or support a worthy idea then you don't necessarily care about how much money you make. I'm not going to give advice on how to manage for a non-monetary outcome. I believe in positive returns, not least because if you run out of money you no longer have the wherewithal to fund worthy ideas.

How would professional venture capitalists invest in super-early companies with small amounts of money if they didn't have the huge amounts of cash potentially needed to single-handedly fund the company through to exit and didn't have gigantic well-known brands? Because that's what angel investing is.

Next: ~~The Life of an Angel.~~ The Work-Work Balance (Angel Investing 2)

On being an asshole

noreply@blogger.com (Jerry Neumann) — Mon, 04 Mar 2013 16:02:00 +0000

Here's something you didn't know about me: I'm vaguely claustrophobic. It doesn't mean much in practice, but when I was at the last TechStars demo day at Webster Hall, I watched the presenters from the same place I watched the Beastie Boys in 1985, the Mountain Goats in 2008 and every concert in between--the back left, right near the door, the stairs, and close enough to the outside to make it tolerable.

It's a little different in the back. Fred Wilson and Brad Feld are right up there in the front row representing, while us riff-raff are standing by the bar wishing it was open. I like the back row. My best friends from college are the ones I met sitting in the back row. When David Soloff came to talk to my class at Columbia, he paused a few minutes into his profanity-laced tirade about entrepreneurship to poll the class: who was uncomfortable with his swearing? Several hands in the front row went up. Who thought it added to the discussion? Several hands in the back row went up.

Some of the people in the back row are the studied cool. But some others are the actually unenthusiastic. The back of demo day was no different. On one side were people like Andy Weissman, Chris Wiggins and Taylor Davidson, all trading notes on which founders we found particularly awesome, who already had funds committed, the amazing amount of progress some teams had made during that session of Techstars, and, in general, gratefully soaking in the condensed learning of months of hard work by talented and smart people.

On the other side of me were a group of people loudly telling each other how ridiculous the ideas were, how the companies were going to crash and burn, how stupid and sheeplike the investors were for giving them money, etc. You know what they were saying, because our ecosystem is flooded with this type of talk. We see it every week in the tech press when some formerly high-flying company starts to falter. We see it every day in the comments on Hacker News. We hear it when we have coffee or drinks.

And it's not just envious wannabes saying these things. I've heard venture capitalists, big company executives, startup employees, lawyers, angel investors, students, and professors bash entrepreneurs. Every sort of person except other entrepreneurs.

Chris Dixon said there are two types of people in the world: people who have tried to build a company and people who have not. This ruffled the feathers of people I know in the innovation community who have never been an entrepreneur because it implies that those who haven't been entrepreneurs should just shut up and sit down. That's not exactly right, but it is true that people who have been through the process of trying to start a company do not, as a rule, engage in destructive and pointless criticism of other entrepreneurs. Not that non-entrepreneurs all do, just that entrepreneurs don't.

There's a difference between criticism and critique. One is destructive, the other constructive. Entrepreneurs who have been through the grinder, who have been "dismissed by arrogant investors who show up a half hour late... having pundits in the press and blogs who’ve never built anything criticize you and armchair quarterback your every mistake" (as Chris puts it) don't then turn around and do that same thing to other entrepreneurs. Because they know from experience that it's pointless and results in pointless pain.

The people who call entrepreneurs stupid, who bludgeon them with their mistakes and try to humiliate them in public rationalize it by saying "we're being direct, open and tough--just like the real world." They are egregiously wrong. That's not the form that either education or motivation takes in "the real world." Unless by real world you mean our schools or government where the highest goal is creating the conformity needed to staff middle management at our large industrial age corporations. Entrepreneurial zeal does not survive that.

I once asked a Swedish founder what the difference between starting a company in Sweden and in the US was. He said that in Sweden there is a saying: "the tallest poppies have their heads cut off." Those who are outstanding will be cut down so they no longer stand out. He believes this attitude prevents many Swedes from deciding to strike out on their own. I wish this were particular to Sweden (no offense)--or to any one place that wasn't here. But it isn't. It's not even a Swedish saying, it's a universal one. It's first recorded use is in some of the first recorded history, Herodotus. The context then was to enforce a more homogeneous community in order to better control it. This is still its use now. This attitude is the absolute antithesis of what we are trying to do in the entrepreneurial community. We are not cutting the heads of the tall poppies, we are letting a thousand flowers bloom, praying that one of them will be taller than all the rest so we can then plant its seeds and someday all the poppies will be tall.

If you've been through the pain of starting a company, you know that criticism is entirely useless. If you haven't, and you find yourself in the back of demo day wanting to cut down the people brave enough to have made it up onto the stage, you need to think hard about it. Think about the difference between criticism and critique. Think about the difference between extrinsic and intrinsic motivation and how entrepreneurship is predicated on the latter--the carrot, not the stick. Think most of all about whether what you are doing and saying is helping founders succeed, even if their success is not something you will be part of. Because if you don't believe that their success helps us all, no matter whether we are involved in it or not, then you are in the wrong room.

At least you're near the exit.

How to kiss your elbow

noreply@blogger.com (Jerry Neumann) — Mon, 24 Sep 2012 14:22:00 +0000

Even before Paul Graham's Growth post the recent VC meme was that entrepreneurs just aren't as ambitious as they used to be. They are too careful, husbanding their cash rather than boldly investing it in growth. I've heard this kvetch four or five times since Labor Day, each time from a smart and well-respected VC. They blamed the ease of raising seed money compared to the relative difficulty of Series A and B money, the incubators and angels corrupt the entrepreneurs.

I've had this conversation with many of my entrepreneurs over the years: the market's going to pass you by, carpe diem, etc. But I never really thought of it as a trend, it was just the usual learning opportunity for first-time entrepreneurs--there's no starting gun, no one is going to tell you when to start seizing the day, just do it. This has always been a conversation in the fifteen years I've been investing in early-stage. Is it really now a wider phenomenon?

I don't know, but I heard it enough that I ran the idea by a couple of my entrepreneurs. The entrepreneurs sighed and rolled their eyes. You advised me to raise just the money I needed to get to the A, they said, Paul Graham says I should "not need money." Which is it, they ask? Do you want me to not need money or do you want me to get aggressive and raise my next round sooner, maybe without the metrics I need to get a good valuation?

Fair enough, the world is full of conflicting advice. And I understand how annoying it can be when it's the same person giving you both sides of it.

And let's be clear: the dichotomy is not necessarily between the lean startup and "go big or go home." Suster makes the case that the latter is not always the best route. No argument. This is more along the lines of when to hit the gas, not if. I only invest in entrepreneurs who tell me they can and want to go big and then I try to get them to stick to what they told me. My favorite question when these conversations happen is "what's the bottleneck?" What can we do, who can we hire, who do we need to partner with or talk to or get in front of to make what we both think can happen actually happen, now?

When I ask this, the entrepreneur always knows the answer. In fact, they've usually been thinking about it night and day. But they also usually want to take it more slowly than I do. They want to take less risk. Once you've spent the money, that money is gone, and if you're too early it's gone for good.

So how do you know when it's not too early?

Christensen tells a story in The Innovator's Dilemma about Honda's entry into the US motorcycle market. Honda's entry strategy, after much examination, was to give Americans what they clearly wanted: large bikes to ride long distances at highway speeds. Honda's expertise was in designing small, efficient engines, as in their Supercub delivery bike. But Honda designed a big, fast bike for the American market and in 1959 sent three reps to live in LA to begin marketing it.

The bikes sucked. At highway speed they leaked oil and burned through clutches in record time. The cost of sending replacements for the warrantied bikes almost put Honda out of business.

To burn off steam the Honda reps used to go out and ride their Supercubs--small, zippy, 50cc bikes--in the hills east of LA on the weekends. Over time people started asking where they could buy one of these 'dirt' bikes. The reps special-ordered Supercubs from Japan for people. After a couple of years of this a buyer from Sears tried to place a bigger order. Honda ignored him. Finally the Honda reps convinced Honda to change direction, that the big bike strategy had failed but a small bike strategy would work. Innovative distribution channels were forged, sales took off, market entry was achieved.

But if Honda had been more aggresive with their strategy in 1959, if they had sent reps to Miami and Seattle and Dallas and Atlanta and Denver and Las Vegas at the same time as LA, there's an excellent chance Honda would have not only failed to enter the market but actually gone out of business. By taking it slow until they had found a product that fit the market, they bought the time they needed for success.

Bit of a buzzword that, product market fit. Mark Andreesen says "you can always feel product/market fit when it's happening." Unfortunately, this is simply not true. Honda took a couple of years to feel it and even longer to properly trust it. In B-to-B startups you can have a lot of buzz and a few amazing clients banging your door down and still have a product that doesn't really do much. Or you can have a product that is absolutely amazing that great clients are beta-testing but that no one is paying for. In B-to-C you can have a hundred thousand users and still be serving nothing but tech industry curiosity seekers. Or you can have millions of members and few users. These are not product-market fit.

There is a case for going slow, to a point. Your product has to provide real value to your users. You need to have a viable business model, know the metrics you need to make it work, and be on the path to meeting those metrics. And then you need a way to get to customers and convince them to sign up and/or pay. You need all these things before you can feel comfortable ramping up the spend. But if customers love your product, if those customers are profitable customers, and if those customers start presenting themselves, either directly or by making themselves extremely easy to get in front of, then you should let them become customers. And if there are more of them than you can get in front of personally, then you should hire a salesperson. If there are more of them than your salesperson can get in front of, then you should hire more salespeople. If you have a product and you have a market for that product, you should stop worrying and start scaling.

In the old hockey-stick curve there is a flat part and there is a steep part. That transition, the elbow in the curve, is hard to see, especially when you're spending all your time trying to run your company. Here's a question to ask yourself: if you think you can double revenue next year, what's holding you back from increasing revenue by 10x? If the answer is that there's no market yet, then keep grinding away at it. If the answer is not enough people or hardware for scaling, then start spending the money on hiring them, today.

The best possible Series A story: "we don't really need your money, but if we had it we could grow ten times faster starting tomorrow." Term sheet before you get home, guaranteed.

Your personal data is not worth anywhere near what you think it's worth

noreply@blogger.com (Jerry Neumann) — Thu, 28 Jun 2012 15:18:00 +0000

I see a lot of Root Markets-like businesses. Companies creating a way for people to own their own data and profit from it rather than letting someone else profit from it. The idea is appealing: other people are selling your data, it's your data, why shouldn't you sell it yourself?

But most of the people I talk to don't have a good answer to the basic business question: can you sell your product or service for more than it costs you to buy or make it? In this case, can you sell personal data for more than it costs to garner it?

Well, can you?

The IAB says that in 2011 there was $31.74 billion in US interactive ad spend [pdf]. There were 245.2 million internet users in the US in 2011 according to Statista.com, using data from Nielsen and the ITU. That works out to slightly less than $130 in ad spend per internet user per year in the US.

Here is a breakdown of this per capita number, by channel, and a guess as to how much is potentially available for third party data sellers:

		$ per	Addressable
Channel		User	Market
Search	47%	$60.84	$0.00
Display / Banner	22%	$28.48	$7.12
Classifieds	8%	$10.36	$0.00
Digital Video	6%	$7.77	$1.55
Lead Generation	5%	$6.47	$3.24
Mobile	5%	$6.47	$1.29
Rich Media	4%	$5.18	$1.04
Sponsorship	4%	$5.18	$0.00
Email	1%	$1.29	$0.97
Total		$129.45	$15.21

The $130 needs to pay for several different functions. The $28 for display, for instance, pays for account management, creative, media planning, targeting, media buying, ad serving, analytics, verification, and--not least--the actual inventory the ad is placed in. I'm guessing that the maximum amount available to a company selling data to target display ads is 25% of the ad revenue*. The opportunity to use data to optimize lead gen is potentially larger, while the opportunity in sponsorship, classifieds and search is pretty much nil**.

If this is right, and given the fuzziness of the IAB numbers, it means that there is maybe $1.00 to $1.50 per person's data per month available to data sellers.

But keep in mind that Google does not need your data. Nor does Facebook. They are a large part of the market. Your data is competing with everyone else's data--first, second, and third-party data--for this $1 per month. And some of the data you are competing with is so closely tied to the awareness generating process that it can't be pried away and placed in a 'wallet' somewhere.

Take context. The context of an ad can account for somewhere between 50% and 90% of its effectiveness. Context correlates to demographics, purchase intent, state of mind, and behavior. If you are looking at a review of the new Mac Book Pro I don't need any personal information to make an educated guess that you are in the market for a new computer. I can confidently put a computer ad next to that article without any other data, and the only way someone else can intermediate my guess is by blocking the content or ad entirely. Same argument different data for Facebook, and for much mobile usage.

This means that of the $1 per month much less is actually available to you as a collector of the data.

The original Root business model was to allow users to own their data and rent it out to people who wanted to market to them. The problem: users think their data is worth far more than $1 per month. But $1 per month is all that is available, on average. To a single company, it's maybe $0.10 at best. And then there has to be a commission paid to the new intermediary--the Root-like company. The user ends up with maybe a dollar a year. Nobody cares about a dollar a year. There's no business model. I could even imagine a world where each user was worth $0.20 a month, but that price is still nowhere near where it has to be to have users take it seriously.

There is a business model for businesses that gather data very efficiently. There are several pretty large companies that do this. But they have figured out a way to gather the data for much less than $0.10 per person and to collect data on hundreds of millions of people. The Root model simply costs more per person than the data is worth.

I spent several years of my life trying to build a business that lets people take control of their own data while still leaving a way for marketers to find them. I believe in privacy. And I believe that marketers finding customers is key to economic efficiency. I would love to see someone square this circle, but the Root model is not the way to do it.

-----
* This takes into account the fact that I think the IAB/PwC revenue number is the amount paid to publishers, not the amount spent by marketers. The amount spent by marketers may be 50% to 100% more than that paid to publishers on average. Hard to know. This is an important point though: marketing is much, much more than advertising. The amount that companies spend on marketing in total is far higher than the amount that publishers make from selling ads. There are companies selling data that sell into this marketing market that are worth billions, they are not the focus of this post.
** The best businesses are the ones where everyone else thinks you're wrong. My saying there's no opportunity means that if you have a way to use data to optimize these channels, you may have an opportunity that no one else has seen. I like those.

Great Riches and Low Theft

noreply@blogger.com (Jerry Neumann) — Tue, 19 Jun 2012 02:42:00 +0000

In early 1998 I walked the open plan floor of what was then one of the largest web development shops. The founder was giving me a tour so I could see the scores of web developers working diligently. They looked the part, the founder looked the part, the place had good energy. I liked it.

The founder was looking for venture capital to expand internationally. He was a much more experienced businessperson than I was and he knew it. At one point he gave me a sly look and said "How do you know that I didn't just hire a bunch of extras to fill an empty office building floor for the day so I could impress you?"

Now I had done my due diligence and some of the people who would have had to be in on that sort of scam were people who had more to lose lying to me than they could possibly gain lying for him. I trusted my due diligence and I knew the company was real. But I no longer trusted him. At the end of the tour I told him we were passing on investing.

He was pissed. He went over my head to the CEO of my company, directly and through common clients. When I was called on the carpet to explain myself I said only that I did not want to work with that founder. I did not say why. The CEO did not give me a soul-searching stare, he did not grill me, or even ask why that would be so. He knew me well enough to let me have my reasons. He just waved me out of his office.

It's an odd fact that our capitalist system--our brutal, unsentimental, Darwinian, sink-or-swim system--relies almost entirely on its protaganists' ethical behavior to function. Our entire economy relies on trust. You probably don't think about this much. Most people don't think about it at all. I think about it a lot. What I do--what all VCs do--would not be possible without the honest behavior of an overwhelming majority of founders. If even 10% of founders decided to start cannily lying the entire startup ecosystem would come tumbling down shockingly quickly.

I hear objections. Let me distinguish between transactions and relationships. Many transactions are entirely caveat emptor: you need to know what you are doing and what questions to ask. Transactions have a simple API and learning how it works is your responsibility. But a business relationship is different: it is too complex, there are too many ways to be dishonest. It is not possible for both parties in a business relationship to verify everything the other side has told them; if they had to the cost of doing so would make it infeasible to have business relationships at all.

There are many gradations and steps between transactions and relationships; navigating through them requires experience. But if you do not trust a person you should not have a business relationship with them.

Some of the oldest business advice in the world: "A good name is better than great riches."* What happens to those of ill-repute? "The sons of men of no name, they were driven out of the land."** In our community a bad reputation results in being driven out of the land. If you're known for not being trustworthy your career amongst the highly interconnected venture capital community is probably at an end***.

The flip-side has always been that our community hesitates to accuse other people of certain types of ethical lapses. I can only think of one time in my fifteen years of venture investing that I have gotten a third-party reference from a venture capitalist that called someone's ethics into question. The closest a VC will come to saying something bad about someone is to refuse to say anything of substance at all. If you don't like someone, you don't have to do business with them. But impugning someone's character can put their life's ambitions at risk. You need to be extremely sure of what you're doing and cognizant of the effect your words might have before you do this. If you don't, you can do a great amount more damage than your dislike of that person deserves.

I won't do business with someone I don't trust. When someone I worked with has turned out to be a liar I have ended my business relationship with them. Luckily I have not had to do that often and not in almost ten years. But likewise I won't have anything to do with someone who puts someone else's life's work in jeopardy by carelessly judging their ethics in public. These offenses--breaching trust and baseless accusations--are two sides of the same coin. The ignominy of the offenders should be likewise the same. If a good name is better than great riches then heedlessly sullying someone's reputation is low theft, and leaves the perpetrator, the victim, and the rest of us equally impoverished.

-----
* Proverbs 22:1
** Job 30:8
*** Every field has different standards for trust. With startups we expect baseless optimism for instance, where in academia this would be frowned on. With startups we expect confident predictions of the future as if it has already come to pass, while in banking this would be looked at askance. People in the community know the norms. And, in our community, are willing to give allowance for the fact that many entrepreneurs were not part of the community before starting their company so may be unfamiliar with our ways. Mistakes made with good intentions are not ethical lapses, they are mistakes.

Response to comments: Training VCs

noreply@blogger.com (Jerry Neumann) — Sat, 12 May 2012 15:10:00 +0000

Many of the comments on yesterday's post were about training future VCs, or not. Both Brad Feld and Fred Wilson said they did not have junior VCs because they did not want to burden entrepreneurs with inexperienced VCs. This makes a ton of sense. But, then, where should experienced VCs come from? Andy Weissman comments that perhaps VCs are best trained by being entrepreneurs.

You either believe that Venture capital is not a profession--i.e. there are no special skills or knowledge needed that can't be picked up as you're doing the job--or it is. If it is then it looks like the best firms are akin to 'boutiques' in other professions. In fact, almost all the firms are akin to boutiques in other professions. Of course, in other professions boutiques are formed by people who were trained at the mainstream firms. If there were no mainstream firms there would be no people to form boutiques.

Law firms train lawyers. Accounting firms train accountants. Banks train bankers. Even advertising agencies train advertising people. VCs by and large do not train VCs. Maybe VC is not something you can learn by just doing VC, although Fred is a prominent counter-example. Professions train professionals partly because they think their professions are important, so they feel the obligation to pass on embedded knowledge to the next generation. And partly because they can skim some of their underlings' earnings (thus the pyramid structure of professional services firms.)

VC does not have the pyramid structure of some professions, like law or accounting, where most tasks can be delegated with oversight to junior people. So it's true that junior people in VC probably would cost more than they generate if they were truly being trained (as opposed to just cold-calling and spreadsheet-jockeying.) But if we care about entrepreneurs, as we all profess to do, we should want not just the best for today's entrepreneurs, but also for tomorrow's.

If you do, and still don't think training VCs is worthwhile, then it must be that you simply do not believe that VCs can be trained, that VC is not in fact a profession at all.

I do not think this is true. The best--in fact almost all--VCs have historically come from one of five places: VC, banking, law, technology firm management, or journalism. Check the VC genealogy to confirm this. (I don't think any journalists are represented there, but Mike Moritz is a prime example.)

Each of these paths teaches people some of the necessary skills to be a venture capitalist, but not all of them. Witness Kleiner's and Perkins' struggles as they started out, making ridiculously wrong bets on markets they did not understand. Or the revealing comment Fred Adler made* about two of his partners that left to start their own fund: "These fellows came out of Citicorp where they were quite senior and they didn't go through [my] intense interrogation" justifying the investments they were making. The implication being that the two partners did not know enough to make good investments and Adler did not feel they would accept his instruction since they were so senior. In other words, being senior at Citicorp had not taught them all they needed to know to make good venture investments. Those two partners must have learned something on Adler's dime though, because the fund they started was Accel**.

Many venture capitalists made similar mistakes early on. The ones that didn't seemed to either have extensive angel investing experience (and so their early mistakes are not part of the record) or they "played the follower strategy" (as Wilson has it) and managed to get into more experienced VC's deals in order to learn the business.

So if specialized knowledge is needed, how to generate it? Kauffman has their Fellows program to train VCs. Andy thinks being an entrepreneur is the best training. I disagree with both. I think only doing the job teaches the job. And since no one wants anyone doing the job who doesn't know the job, this means a long apprenticeship. But the best VCs seem to not be interested in having apprentices. So, then what?

In my opinion, if we want better trained VCs, then either the culture has to change so VCs feel an obligation to train the next generation***, even though it costs them money, or the LPs need to start looking out for their future returns in addition to their present ones and compel VCs to have a bench. It would be interesting to hear from experienced venturers how they learned the business.

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* Quoted in John Wilson's The New Venturers.
** Wilson's book was published in 1985, Accel was founded in 1983, so Wilson had no way of knowing that Accel would go on to be one of the premier venture funds. This just makes the quote that much better.
*** I would be happy if VCs would even just blog more with other investors as the audience, instead of writing the same frickin how-to posts for entrepreneurs over and over. The world does not need another "How to Read a Term Sheet" post, it really doesn't. It could, however, use a few more "How You Will Get Screwed if You Write a Bad Term Sheet" posts.

On fixing VC ourselves

noreply@blogger.com (Jerry Neumann) — Fri, 11 May 2012 18:59:00 +0000

What good is it for me to sing helplessness blues
Why should I wait for anyone else?

- Fleet Foxes, Helplessness Blues

That's for Fred Wilson.

In his post last month "Can the Crowd Be More Patient", Fred says

We need new medical approaches to preventing and/or curing disease. We need new scientific approaches to generating, storing, and being more efficient with energy. Maybe we need more space exploration. Maybe we need more undersea exploration.

He says this in the context of not being able to fund these things because that is not what venture capital is. But you know what? At this exact point in time Venture Capital can be whatever Fred says it is. If he wants a 20 year fund instead of 10, he could raise it. He wants an evergreen fund? He can do that. I think he could probably raise a fund to do whatever he wants.

So I'm not sure what he's saying. But if what he's saying is that these things are not fundable, no matter the time frame, that they are simply bad early-stage investments, then I strenuously disagree. Investing in the things that make our collective lives better--the very things we think of as progress--should be the only good investments. Venture capital is a means to an end, that end being the commercialization of innovation that makes our lives better.

Here's a thought:

Entrepreneurship is a self-actualizing and a self-transcending activity that—through responsiveness to the market—integrates the self, the entrepreneur, with society. Unavoidably, therefore, entrepreneurship is an exercise in social responsibility. To suppress or constrain innovation and improvement—and their implementation—ignores a society’s needs and wants, holds it back, and diminishes its future. Entrepreneurship is the unique process that, by fusing innovation and implementation, allows individuals to bring new ideas into being for the benefit of themselves and others. It is sui generis, an irreducible form of freedom.

That's from the Kauffman Foundation's 2008 report on Entrepreneurship in American Higher Education [pdf]. Meanwhile, this week Kauffman had a new report [pdf] that--as Ed Zimmerman had it--blames investors in VC funds for being co-dependent enablers of bad VC behavior (for the tl;dr, see Fred Destin's excellent post on the report.) I've heard a lot of opinions on this report: some agreeing, some denying Kauffman's conclusions (for instance, Brad Svrluga's rebuttal.) But while the degree to which venture investors are doing a bad job is arguable, the fact that, as a whole, we are is not.

Nice as it would be to agree with Kauffman and say "I'm doing a bad job because I'm being managed poorly," that's no excuse. Every VC I know complains about bad practices in the industry, because bad venture capital practices affect us all. And while the bad behavior might make short-term economic sense, as outlined in Kauffman's report, I am not in this for the money and neither is anyone else I know.

Yes, I want to make money; in fact, I need to make money if I'm going to keep investing, I'm also competitive by nature and making money is how we keep score. And then, if it's true that the market ends up choosing companies as winners because they are the ones that contribute most to societal growth, then making money is not a bad metric in the long-term. But the real reason I'm in the business is that I want to contribute, I want to be useful. "Entrepreneurship is an exercise in social responsibility." That's what I want to enable. Every good VC I know feels the same way, but almost all of them feel helpless to change the current broken incentive model.

How would we do that, as venture investors? I'm sure there are smarter people than me thinking about this, but here are a few ideas.

Change LP Behavior.

Professionalize VC.

comment

Think bigger.

When Will this Low Innovation Internet Era End?

Has the Internet Run Out of Ideas Already?

calls a bubble

As an industry, we are funding too many ideas which do not make a difference. We can take pride in helping build companies that create jobs. But creating jobs is not as good a goal as we make it out to be if those companies and those jobs disappear three years later. Jobs come and go, but technological progress is forever. Funding progress makes a difference. This is not a "they promised us jetpacks" rant. Jetpacks are stupid. I don't want a jetpack. I don't want you to have a jetpack. I think all of us having jetpacks would not make the world a better place in the least**. That's not progress. Google was progress. Twitter is progress. These are tools that enable us to think better, to communicate better, to find the things we need to know more efficiently.

Frighteningly Ambitious Startup Ideas

industries

That

Kauffman's report implicitly suggested that there should be only 20 funds, each of $400 million or less. If this advice were taken, the venture industry would be a fifth the size it is today. Almost all VCs would be out of jobs. Entrepreneurs would be back in the bad old days when ARD funded DEC with $85,000 and received 70% of the company in return. No one wants that, except maybe the LPs, but that's what is in the cards if that's what it takes to make the investment class work. To avoid that, we--the venture investors--need to do better and we need to do it preemptively.

We are not helpless, we should not wait for anyone else.

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* Many small companies do make a difference in people's lives, and certainly do so in the aggregate. But in some sense it's just as much work to build a small company as a big one. My philosophy is to aim for the moon and land on the roof: a big idea can produce a moderate size outcome or a big outcome; a small idea can produce a small outcome and that's it. Many entrepreneurs I've worked with have showed up with a modest idea. I've pushed them all to be wildly immodest--there's always a big idea surrounding a small idea, go for the big idea.
** Just go buy yourself a Ducati.

*** My current bets are in banking, mobile telecomm, and, of course, advertising.

Venture Capital Family Tree

noreply@blogger.com (Jerry Neumann) — Tue, 24 Apr 2012 18:40:00 +0000

About six months ago my friend Chris Fralic (@ChrisFRC) invited me to a screening of Something Ventured, a film about the origins of the US venture capital industry. Definitely worth checking out. One of the things it got me to thinking about was how intertwined the early VC firms were. So, in the spirit of one of those genealogies of rock music posters, I gathered some data and made a visualization. It's not pretty like the rock and roll one. And it's woefully incomplete, which I need your help on. We'll get to that.

The whole thing

Zoomed in on some interesting '90s reshuffles

I used jquery and d3, although I had to customize d3 a bit. Because it's d3 and there are a lot of svg objects, it could be slow on slower computers. Also, screen size makes a big difference here, not recommended for mobile viewing.

I was trying to put in firms from the early days and firms that were critical links between the early days and today, so there are a very few firms founded in the last ten years in there. It's a historical study, not a contemporary view. The founders of the firms are noted, but not seminal later partners (i.e. Kleiner and Perkins but not Doerr or even Caulfield.) Although new partners can have a huge impact on a firm's direction*, I just didn't have time. Maybe in the next iteration.

Firms founded in New York are blue, in Boston are red, and in Silicon Valley are green. Others--including those that do not yet have an entry for place--are orange. Type a firm name or founder into the box (there's autocomplete) and click to zoom in on that firm. Also, pan and zoom using the mouse.

Venture firms never really die, they just fade away. And some firms stop being VCs (in the '80s many firms abandoned venture for PE) or were financial orgs and became VCs. This is denoted by a 'tear' at the beginning or end of the firm's bar--the firm had a life before or after, but was not an active venture investor.

I've also started adding noteworthy investments, but there are only a few. As far as I can tell, there is no extensive list of who backed who when. Which brings me to my ask.

I've put in info as I came across it for the last six months, but I have other commitments, so it's been slow. And the easy info sources are running dry. So I slapped on a form, hoping you all would help. All contributions are welcome, but in the spirit of the thing, I'd like to prioritize adding firms that were either critical links between the past and present, that trained a bunch of people who went on to found their own firms, have been influential for a long time, or were influential in the past and have disappeared (i.e. TVI, MPA&E.)

When contributing investments made by firms, I would rather not add every investment. I've tried to add investments that were important or household names. This is a public historical document, I think it's more interesting (and puts the better foot forward) to show that Starbucks and McDonnell Aircraft were venture backed (or Pizza Time, for that matter, even though it failed) than, say, Kozmo.com**.

To contribute either click on the '+' button on the upper right to add a new firm, or click on the name of a firm to edit/augment their info. When you hit 'submit', it should reflect locally, but it doesn't add it to the database (I'm not a back-end guy) it emails me. I will edit and add data, I don't expect to get a ton of submissions. The data is open source (cc by-sa), and any contributions will be considered open as well. I will add your name to the contributor list on the help page if you put it in the 'Comments' box on the form (there's no other way for me to know who you are.) Also, put your email address there if you want so I can contact you re your submissions.

But please, do submit! It struck me as odd when doing the research here how little the venture community values its roots. Law firms have web pages and sometimes whole self-published books celebrating their founders and history. Your typical VC firm comes across as if it's in the witness protection program. It's crazy that I can't figure out who all four founders of Menlo Ventures are and where they came from, or who backed Federal Express and when. I've got decent google-fu, and I looked, trust me. Someone out there knows, and you should enter this stuff. The mainstream industry is now some 50 years old. We are in danger of losing our past.

If someone knows of a source of data for this (that is either free or you can get me access to), I will port stuff.

Primary sources were firm web sites, Wikipedia, and The New Venturers by John Wilson, a great book now out of print. Some data was taken from Venture Capital at the Crossroads, Creative Capital, Valley Boy, The Startup Game, and Elfer's Greylock. I'm planning on skimming Done Deals and Venture Capitalists at Work for more. Other sources are in with the rest of the data as 'cites'.

-----
* In a couple of case, Paul Bancroft joining Bessemer from DG&A, for example, I think it was significant enough to consider that the start of Bessemer's venture activity, even though that is not strictly true.
** Well, hard to say. I can only think of interesting companies because I only remember the interesting ones. Kozmo might actually be an interesting investment from a dot-com bubble point of view. Maybe just send me whatever you want and I'll figure out some way to highlight some and not others. I don't know.

That joke's not funny anymore

noreply@blogger.com (Jerry Neumann) — Thu, 19 Apr 2012 16:23:00 +0000

"[Y]ou have to assume that humans are capable of looking at facts, finding root causes and formulating solutions. On my planet there's not much evidence to support this assumption... If humans had the ability to look at facts and make good decisions, think about how different the world would be. There would be only six kinds of cars on the market and nobody would buy a car that was second best in its price range. There would be no such thing as jury selection since all jurors would reach the same conclusion after viewing the facts, and all elections would be decided unanimously. That's not the world we live in. Our brains are wired backwards. We make decisions first--based on irrational forces and personal motives--then we do the analysis. The facts get whittled until they fit into the right holes."

-- Scott Adams*

[The first section of this post was previously published on AdExchanger, and there's an excellent comment thread there, so you should go read it. This is the rambling version.]

Jokes all start with one of a few stock set-ups. "A man walked into a bar." But the punchlines are all different. VC pitches are the opposite: the set-ups are all different, but the punchlines are all the same.

Stop me if you've heard this one before. "We enable the half of advertising that is not yet online: brand advertising!" Been hearing that one for more than ten years now. It permeates the hopes and dreams of every adtech entrepreneur and investor. And still no one has cracked the code.

My friend Tim Hanlon got together with Tim Chang a few weeks ago over on AdExchanger to offer some reasons why this might be. Worth your time, but here's the tl;dr**:

No standards or consistent measures of “success” other than outdated or inadequate metrics like CPM and CTR;
Limited real-time intelligence;
Unsuitable display ad formats; and
Lack of creativity in formats.

The prize is huge. As Tim and Tim point out, two-thirds of advertising spending is brand advertising, but online only one quarter is. In fact, if brand advertising dollars moved online in the same proportion that sales advertising has, it would almost exactly close the famous gap between time spent online and ad dollars spent online. The $50 billion gap that Mary Meeker mentions is exactly equal to the missing brand spend.

So I understand the urgent desire to figure out online brand advertising. If we did, we'd more than double the online advertising market. Online pubs would rejoice, online marketing pros would have more excuses to go out drinking with prospective clients, my portfolio value would quintuple overnight. Good things all. And I appreciate the optimism that Tim and Tim have, their willingness to keep suggesting solutions. But I think it's the triumph of hope over experience. Each of these things has been tried, and tried and tried. And still we believe that this time it's different, that this year an online branding play will work. Online video maybe, or Facebook, or Pinterest. Every new company is touted as the one that will make branding work online.

But what if we try all these things, like we've tried everything before, and they don't work? What if we eliminate all the possibilities and what remains is... nothing? I'm going to be branded a heretic for saying this, but what if online just doesn't work for branding?

I mean, not to be defeatist, but we understand branding pretty well. Marketers have been creating brands nigh on one hundred years now, it's not a black art. And the solutions I hear, even Tim and Tim's, are not untried. More, they are not what makes brand advertising effective in other media. I don't buy that these are the solutions. I think it's distinctly possible that there are no solutions.

Maybe the medium itself is antithetical to the way brands are built. Like direct mail, maybe the very fact of delivering your message in a low-budget, specifically targeted way can not in any way build a brand. Brands attempt to exist autonomously, they are objects of desire, they want to distinguish what otherwise is indistinguishable. The psychological processes of branding are inimical to the idea that the brand has been chosen for you. Brands do not choose you; you choose brands. Brands are aloof, they aspire to be the Platonic ideal, their competitors just shadows.

Perhaps. I mean, I could be wrong. It could be that even though we sell ourselves to clients as brand-building geniuses, we don't know what we're doing; that we're groping in the dark, throwing random darts and just haven't hit the bulls-eye yet. We could be a bunch of monkeys at typewriters and Shakespeare will just roll on out one day. Could be. But it seems unlikely.

What if I'm right? What if online branding is a mug's game? If it is, it won't be too much longer before marketers get wise and just stop listening to online branding pitches. Maybe they already have. Maybe they never did listen to them. What's the fallback plan? How do we go about getting the brand advertising dollars if online brand advertising doesn't work? What can we do that will cause brand advertisers to move their branding dollars out of advertising altogether into some other online channel? How do we disrupt branding?

*****

What is branding, really? Why does it work? For the marketer, branding is a way of wrapping all of a product's attributes in a neat package and giving it a handle so they can refer to it easily. For the consumer, brands are a shortcut: for products where the potential benefit of making a choice is smaller than the cost of choosing, a brand is a fallback. Brands are Scott Adams' whittled down facts, except that marketers have done the whittling for us so they can control the outcome to their advantage. The hole they fit into is your brain. And research shows people only have a few of these holes in their brain.

This can work in a couple of ways. A consumer confronted with a dozen pasta brands in the spaghetti aisle*** would have to expend some time and effort deciding which was best for them. The small potential benefit from finding a better quality pasta is less than the cost in time and effort to determine this, for most consumers. So even if De Cecco is a better pasta, it is a rational for someone familiar with Ronzoni to buy Ronzoni. The pastas are similar enough that someone who just wants a bowl of spaghetti should not expend any effort distinguishing them: just choose your brand and move on.

On the other end of the spectrum, some things are extremely costly to evaluate. Choosing a motorcycle, for instance. The variables that come into play include not just the motorcycle itself, but complementary goods like service quality and availability of third-party components (if the stock pipes are too tame, say.) There are also intangibles, like aesthetics, community, and how you will be perceived among your peers if you are riding a Honda instead of a Harley. A brand can ensure that, even when the objective technical qualities of the bike itself are the same or inferior, it has an advantage among certain consumers because the cost of objectively evaluating differences between bikes is, for most people, impossibly high.

This cost/benefit analysis masks another obvious aspect of branding: risk-mitigation. I have, driving down the highway with my kids, chosen McDonalds though this would be at other times not on the list of possible dinner spots. But I know exactly what I'm getting, how long it will take, and how much it will cost. Because there's a fixed cost of investigating new options, even if for one-time use, the risk/reward curve is not linear.

The answer seems obvious. If branding is a needed compensation for something our brains are just not good at, a low quality way to reduce search costs, an easy alternative to remembering tons of facts, then the answer is to provide a better, more efficient way to sort alternatives. The internet, in its ability to instantly connect you to huge data sources and extremely fast algorithms no matter where you are and what random question you're asking, seems to be the perfect answer.

This is what computers are good at. Lots and lots of data, changing prices, personal utility curves. Right now I might walk into the supermarket looking for a relatively healthy breakfast cereal that my kids will eat. Given the huge number of choices, I might settle on Frosted Cheerios (even though they're probably about as healthy as a glazed donut) because Cheerios has pounded the idea that they are healthy into my brain. I can imagine, instead, walking into the supermarket, scanning the Lucky Charms with my smartphone and asking it to rank healthier alternatives for me. I can imagine a world where I tell an application what I like and dislike about my current pair of sneakers and it recommends a pair that would be better for me. I can imagine a world where I enter the specs and spec tradeoffs for any good imaginable--skis, cars, laundry detergent--and my computer finds me the best match.

But I'm not leading you down a garden path here. I don't do Socratic dialogue. I do not know the answer to the question I'm asking. I do not think these ideas will work because nobody will pay for them.

*****

Generally, and certainly with advertised goods, the seller is the one paying to find buyers and not vice-versa. This has resulted in all sorts of market distortions. Sellers are motivated to sell, and not necessarily only if the product is right for the buyer. That the seller is paying to find buyers--any buyers--instead of the buyer paying to find the perfect seller is a bit of an historic accident. The media was once solely a broadcast mechanism, a mass-reach vehicle. Before the internet, seller-financed advertising was cost efficient while buyer-financed search was cost prohibitive. Even though that is no longer necessarily true, advertising is stuck in a local maximum.

It would certainly be more systemically efficient today if consumers decided what they wanted and then went out and searched for their best match themselves. Then advertising would be less effective so there would be a lot less of it. If sellers did not need to advertise, they could lower the cost of the product and this lower cost would--I'm guessing--more than compensate buyers for the time needed to find the right product. The buyer would end up even on cost (lower product cost ~= higher search costs) but with a more appropriate product. That's the ideal world, but it requires massive behavior change from both sides of the market at once. There's no way to achieve that kind of coordination.

As long as advertising continues to be cost-effective, sellers will advertise. As long as they advertise, they will not lower prices. And as long as they don't lower prices, buyers would have to pay twice if they decide to do the search themselves: once for the advertising and once for the search. This is a long way of saying that no one except the sellers themselves will pay for anything to do with informing consumers about products and services. We are stuck with what we have, efficient or no.

Want to quibble? We now have some seventeen years of evidence that, even if it's a better way of doing things, consumers will not pay for search in any way other than by looking at ads. This is, if you think about it, probably the most bizarre thing about internet marketing. People pay for media that compares and analyzes products, but in a way that undermines the value of these comparisons. Yelp, Google (like Car & Driver magazine offline) critique the very industries that finance them. Their interests are in question. Marketers are attempting to influence people right as they are trying to make uninfluenced choices. Search for a product on Google and you are inundated with ads. Odder, many are clicked. People are searching for someone to convince them, they are going through the motions of choosing and then avoiding making choices. The media soothes the cognitive dissonance with a pleasing veneer of objectivity, but the objectivity is--has to be--a sham. Follow the money.

The non-profit Consumer Reports has overcome this criticism by refusing to accept advertising. But they may be the exception that proves the rule: despite almost certainly being worth the subscription price for anyone who buys even one thing in any category they cover, they only have some seven million monthly subscribers. Consumers will not pay to inform themselves. That's why we're stuck with marketing.

*****

Some other, possibly spurious, correlations to note:

	TV	Print	Online Display
Measurability	Low	Medium	High
Involvement	Absorbed	Absorbing	Engaged
Audience	Mass	Select	Targeted
Branding	Yes	Sure	Not so much
CPMs	High	OK	Low

Many intelligent observers, when contemplating low CPMs or recalcitrant brand advertisers say we just need more measurement, more engagement, or more specific targeting. But these things seem to go the wrong way. On the other hand, there are some exceptions: the trade press is more targeted and has higher CPMs; search is more engaging and has higher (effective) CPMs; etc. So the point here is not that we're doomed, but that the easy answers will not do--we're probably analyzing success along the wrong dimensions.

*****

Regardless, I believe in the power of the internet. I think that we can achieve a better product-consumer match by using personalization, community, data and machine learning. In fact, this seems almost too obvious to say. The internet has the power to create a much better branding mechanism: one that works better for brands and for consumers.

I also believe that brands can be valuable. They are proprietary marks, so can guarantee implicit promises and ensure repeat business. They allow trust, and trust is a necessary lubricant for commerce. If there were no newspaper brands, no one would read newspapers, because they would not be able to judge the quality of the news they were reading. If there were no retail brands, every purchase would be like walking into a generic electronics storefront in Times Square: buyer beware.

My objections are not to the internet or to branding. My objections are to the way we are approaching disrupting**** branding. I do not believe the success of online brand advertising is about waiting a bit longer, or measuring better, or creating more engagement. We've waited long enough, we measure better than any other medium, and we are as interactive a medium as they come. If you are espousing those ideas, then you have to also explain why you are right now when you would have been wrong all these long internet years. Things do change, but sudden change is either because of a compounding effect or a catalyst. It does not look like to me that online brand advertising is increasing in an exponential way. Nor do I recognize a catalyst*****.

Or, and I think this is a more promising path, we need to accept that branding may not change to accomodate us, we may have to change to accomodate branding. No more complaining that brand marketers just don't get it. No more waiting on incremental change in measurement or attribution technology. Find a way to allow brands to hone and prove their promises, while giving them a much larger payoff for doing so. Don't think about how to service Procter & Gamble or Coca-Cola--disruption starts off by creating new markets, not servicing old ones--think about how you could help a quality product or service build a brand from the ground up for far, far less than a TV branding campaign would cost. If you do that you will have the big brands' attention, and an amazing business.

-----
* Quoted in Bruce Tremper's Staying Alive in Avalanche Terrain, a must read if you like the backcountry in Winter.
** Seriously? What are you doing here?
*** I was in a supermarket in a hispanic part of Pennsylvania recently where pasta was in an aisle labeled 'Ethnic' while the Goya black beans were in an aisle labelled 'Beans.' Where I live in Hoboken, the exact opposite is true. I wonder if there's a place where the ethnic aisle stocks Oscar Meyer and Easy Cheese.
**** I wrote a typically long blog post on disruption and what it means in this context here.
***** A catalyst has to be a new technology or an entirely new way of utilizing it. The internet itself, say, or social media, or collective intelligence, or online video, or data-driven matching. These could all have been catalysts but, as it turned out, they were not.

Selecting, not filtering: Give me a reason to say yes

noreply@blogger.com (Jerry Neumann) — Tue, 28 Feb 2012 16:43:00 +0000

Raising money for my last startup was humbling, frustrating, time-consuming. But that part was okay: any highly selective process will be humbling, frustrating, and time-consuming. The part that really bothered me wasn't that it took so much time, but that so much of that time was a complete and total waste. In almost all of the VC meetings, we did not leave with a check. But in some 80% of the meetings we also did not leave with any insight as to why not*.

The best VCs listened to us and then gave us some insight into their thinking. Fred Wilson and Brad Burnham actually said no to us and then worked through their thinking about what we were doing in great and helpful detail. Josh Kopelman and Howard Morgan told us it wouldn't work, told us exactly why, then invested, and--after that--introduced us to people who helped us fix the flaws in the plan. But many others gave us either no response at all ("we'll get back to you") or generic non-responses ("we'd like to see more traction.")

We had a pretty firm idea of the problem we wanted to solve, but we were somewhat flexible about how we would solve it. We used the feedback from the money-raising process to hone our ideas. When we got no feedback, we felt we had given the VCs critical market intelligence and gotten nothing in return.

One of my ideals when I started investing was to always provide feedback when I said no. But here I am four years in, going through the pitches that piled up last week while I was on vacation. I'm finding it hard to live up to that ideal. I'm saying no to companies that I don't have a concrete reason to say no to. After a bit of introspection, I think that finding a reason to say no is not really how I make the hard decisions.

I have a tangible reason to say no to some 85% of the pitches I see, and I say yes to less than 2% (some of these I don't end up doing because we can't agree on a deal.) Here's a swag at how my dealflow works out:

40%: No; I do not know your market well enough to help you succeed (also known as I do not know your market well enough to make a good decision about investing);
20%: No; I do not think your idea will work and I can't see where else you will be able to put the technology you're building to work/you are completely inflexible about entertaining other potential markets for your technology/you are too flexible about where you will put your technology to work (the "we're a platform!" syndrome);
10%: No; You are creating something merely better, not different;
5%: No; You have the wrong team/your team does not seem to gel/you do not seem to think you need a team at all/you are coding in .NET;
5%: No; Other explainable reasons;
5%: No; Bad**;
13%: Meh;
2%: Like.

I always explain, in as much detail as the entrepreneur wants, my thinking behind the 85% where I can say no. And I am always happy to explain why I like the 2% I like.

The rub is in the penultimate 13%. These are companies that I don't have a real reason to say no to, companies where I analytically think they have a venture-capital-winner expected value but where I just can't get excited about them. The reality is that with these companies--and, in fact, with all companies--I am not looking for a reason to say no; I am looking for a reason to say yes. With the 85%, there is a glaring reason why I can't say yes. With the 13%, I just can't get the word to come out of my mouth.

For the companies I can easily say no to, some dimension of their plan (team, market, vision, product, customer, etc.) does not rise above my threshold of yes. For the 15%, all aspects do. Analytically the fitness function then necessarily also rises above my threshold.

The difference between the 'meh' and the 'like' is that the 'meh' companies are good enough in all aspects but not great in any of them. The 'like' companies are the ones where they really excel in at least a couple of ways: a great team, a big market, a compelling vision. I try to select not just for how good a company is, but how good it will be. It's easy to improve along one dimension, it's possible to improve along a couple of dimensions, but it's almost impossible to improve along all dimensions. The companies that are just good enough in all dimensions need to improve in all dimensions. The companies that are great in a few just need to improve in a few others, not all, to be great overall.

In fact, some of my favorite companies are the ones that may not even rise above the threshold in one or two dimensions but make up for it by having a superstar team or a gigantic market or a world-beating vision. These are the companies that have a shot at being legendary.

I don't know what to say to 'meh' companies after they pitch me. It's hard for you to recover from a "we're not so bad" pitch. But if you're dreaming up your startup right now my recommendation is to be good at everything, but to be insanely great at something. That's what gets me excited.

-----
* And, I should note, the founding team knew the venture market inside and out. We had done our research on which firms to approach based on what they were interested in, which partners to approach, had pre-sold the idea before the physical meeting, had customized the deck to highlight the aspects that particular firm/partner could grab onto most quickly, etc. Highly suggested in any case.

** My dealflow right now is pretty highly curated so I don't get a lot of pitches that are just, well, bad. Not to be judgemental. Bad, to me, is a founder who simply does not know what they're doing: a non-coder trying to enter a market either (i) that they just don't know anything about--generally where they've had a bad customer experience but have not done the research to understand the institutional framework behind the root cause, (ii) where there are great companies already doing exactly what they want to do and they've never heard of them, or (iii) that is so small that even revolutionizing it will create almost no societal value. Or, they could give a damn about creating societal value, they just want to make some money quick.

VC/Company Investment Visualizer

noreply@blogger.com (Jerry Neumann) — Tue, 17 Jan 2012 19:09:00 +0000

A friend asked me last week if I knew a tool to help him visualize which VCs were investing in a sector. I did not. But I realized I could pretty quickly repurpose the VC Bar Chart code and some unpublished code that pulls in data from a Google spreadsheet to show a force-directed graph. So, weekend project.

Data from Crunchbase, visualizaton using the d3.js library.

Here's my portfolio.

The site is here. Just start typing company names in the upper-left hand corner box and hit plus to add. Real name to Crunchbase permalink translation uses the list of companies as of Friday* or so, so if the company was added to CB later, autocomplete finds nothing; just type in the permalink and the company will still be added. In the screenshot above a few of my companies had no CB investor entries, so they're just floating out there. Many of my other companies are not linked to me because CB does not mention me as an investor.

One way to explore is to enter a bunch of companies in your area of interest and see how the graph falls out. Here's one of the AdTech industry.

The save functionality is experimental (to me, that is.) It uses HTML5 localStorage. The caveat is that you can't email visualizations around that way, and there may be times when your browser clears localStorage (sometimes when clearing cookies, for example.) If it does, you lose all saved visualizations.

The code is all client-side, so it's right there in your browser if you want to look at it. I found myself late last night using a non-analytical debugging process** when I was trying to get the 'load visualization' piece to work. I'll put it up on GitHub some time after I clean it up.

-----
* And I redacted the list to only include companies that CB showed having investors. The full list was too big to load efficiently.
** Mainly making random code deletions.

You can't manage what you can't measure. Not at scale, anyway.

noreply@blogger.com (Jerry Neumann) — Fri, 02 Dec 2011 19:38:00 +0000

A year ago I wrote, re investing in social marketing, "The social loop will share superficial characteristics with the display loop, but it's really completely different... the area with the most near-term leverage will be tools that help communicators understand the impact of how they are communicating and then help them make better decisions." This has turned out to be completely true.

I've been thinking about social marketing for five years. It has seemed obvious that major advances in marketing technique will occur through the social channel, but it was never clear to me exactly what those would be. I looked at and worked with a couple dozen social media marketing companies before throwing up my hands and declaring non-prescience.

My rule of thumb is that when the evolution of the landscape seems unknowable it is usually because the technology that will underpin the advance is still in flux. The obvious solution is dropping a level deeper in the stack and looking for investments there. In mobile, that meant Flurry four years ago and Media Armor a year ago. In social, it meant Awe.sm.

The smartest guy I ever knew in the ad business (like being the tallest dwarf, I know...) said, of managing people, "Whatever chart you put on the wall goes up."

-- Clay Shirky

That was me, the tallest dwarf, from back when I knew Clay, when he was just another guy.

I worked at IBM during the heyday of the Six Sigma movement. I was a design engineer, trying to optimize a very small piece of the central processor of what became the System 390 series of mainframes. As a design engineer there were several layers of abstraction between me and the silicon: the design language was a visual one--I wrote a flowchart which was compiled into a set of logic gates which were then mapped onto silicon. Aside from tweaking the logic gate-level design to try to get better performance, I spent my time at the flowchart level, as did most of the engineers.

Six Sigma methodology has you measure processes, find causes of errors and remedy them. The idea is to improve processes until there are fewer than 3.4 defects per million. IBM had a company-wide mandate to implement Six Sigma. I was subject to this mandate.

I asked my manager how I was supposed to measure my 'defects' and why would I even want to if I had to define them in such a way that I essentially never, ever made that type of mistake. He said "How are you going to improve if you aren't noticing your mistakes and figuring out how to stop making them?" "I already do that," I said, "I'm just not marking them down on some stupid piece of graph paper thats been pre-printed with a normal curve." He said "But then how can we manage it?"

Ah, Bach.

You can't manage what you can't measure. Stupid as managing designers on the binary idea of defect/not-defect and on such a stringent scale, constantly knowing how well you are doing so that you can constantly improve is extremely powerful. This idea, probably more than any other, drives my investment strategy: things that are not being measured are being managed poorly; creating new ways to measure creates ways of doing things immensely better, it creates entirely new businesses.

The fact is, you do get what you measure, whatever graph you put on the wall will go up. But the moral of that pithy aphorism was meant to be: be careful what you wish for.

If what you are measuring in social marketing is Likes or Follows, that is what you will get. But how closely aligned are these measures with what a business really wants: happy and loyal customers, higher sales? You don't know. No one knows. This particular loop hasn't been closed. Because the social gesture cause and business result can't be tied together in a measurable way, it can't be managed and it can't be improved.

I invested in Awe.sm's seed round because they provide core social measurement functionality, the ability to tie social actions into their actual results, to close the loop. I re-upped into their Series A because they're now doing something even more interesting: they're providing this functionality to other developers via API. Instead of being just an analytics player, they're now enabling the creation of an entire social marketing infrastructure that can use measurement to provide a ever-improving feedback loop.

I may have gravitated to marketing in part because dealing directly with people is too messy to ever even approach Six Sigma, but the engineer in me still believes that by measuring you can improve, and by linking measurement and algorithms you can create a feedback loop that allows you to improve adaptively and in real-time. This idea has revolutionized online advertising over the past few years. It's going to revolutionize social marketing over the next few.

iMapBox

noreply@blogger.com (Jerry Neumann) — Wed, 23 Nov 2011 15:37:00 +0000

I've always been the type who, when confronted with a one-hour task, will instead take two hours to automate it. Here's an example.

VCdelta is my bot that tracks additions to VC portfolio pages. It has its own twitter feed. Its twitter feed is about to surpass my twitter feed in number of followers. It seems my bot is more interesting than I am. I thought it would be interesting to graph the number of people who have followed me versus the number of people who have followed VCdelta over time. Twitter does not provide stats like that, but whenever I get a follow email from Twitter, I hit archive, not delete. So all I needed to do was count the follow emails by month.

Turns out Python doesn't have a very good library for using a mailbox as a data source. The Python email libraries assume you are planning on writing an email client. So I wrote an abstraction layer for the Python IMAP library. Code is here*.

Here's the code to count twitter followers:

import IMapBox 

me=IMapBox.IMapBox("imap.gmail.com",my_acct,my_pwd)
mymail=me["[Gmail]/All Mail"]

myfollows=mymail.frm("twitter").subject("following")

mydates=[myfollows[x]['date'] for x in myfollows]

The 'me=' and 'mymail=' open a connection to my email account and select a mailbox, in this case the All Mail mailbox. (The command 'me.list()' lists all the mailboxes for the account.)

The next line filters mymail so myfollows is only emails from Twitter that have 'following' in the subject line**. iMapBox is lazy--it doesn't fetch the emails itself until it has to--so this is pretty fast. myfollows acts like a dictionary, so you can len() it, ask for the keys()--these would be the message IDs--or the items(), iterate over it, or get items.

Each of the items in the dictionary is an email message. These also act like dictionaries, with keys like 'from','to','subject','date', and 'text'. The next line creates a list called mydates of the date each follow email was sent. It does this by iterating over each item in myfollows and pulling its date out. This is the slower part: when you set up an iterator, iMapBox gets all the headers***.

The part about counting follows per date I will leave as an exercise to the reader. Here's the graph of my follows and VCdelta's follows. I've been tweeting for some three years, VCdelta for six months.

On a sidenote, this is a logarithmic scale. The green line is my trend. This is odd, no? I mean, I'm not getting exponentially more popular, so this argues that a lot of follow behavior is algorithmic of some sort. I had expected more linear growth. I also expect VCdelta to level out soon, as it reaches the limits of its natural audience.

Another example, email volume over time:

You can see where I started using my current email account full-time, in September 2006. And you can see when I started investing full-time, in mid-2009. And you can see why my email response time has slowed dramatically.

The code:

from datetime import date, timedelta
import IMapBox

me=IMapBox.IMapBox("imap.gmail.com",my_acct,my_pwd)
mymail=me["[Gmail]/All Mail"]

for yr in range(2006,2012):
 for mo in range(1,13):
  beg_month = date(yr,mo,1)
  end_month = date(yr+mo//12,mo%12+1,1)-timedelta(days=1)
  print mo,"/",yr,"\t",len(mymail.dates(beg_month,end_month))

This is an alternative way to count emails per month, filtering by date instead of collecting dates. The 'dates(x,y)' method filters the emails for only those that were received between date x and date y (inclusive.) This is faster because even the headers are never fetched.

Some other ways to use it:

c=mymail.frm('josh')+mymail.frm('matt')
d=mymail.frm('josh')-mymail.to('matt')
e=mymail.today()
f=-mymail.today()

The first is all messages from either Josh or Matt. The second is all messages from Josh that aren't also to Matt, the third is all today's messages, the fourth is all messages except today's.

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* I'm an electrical engineer, not a computer scientist. So I can build a waveguide to your specifications, but I'm not entirely sure that this code is all that good. Please, feel free to fork, suggest improvements, make improvements, tutor me on garbage collection or unit testing, whatever.
** I like object chaining. I know it's not Pythonic, but I'm not sure why. It strikes me that since I don't really understand too deeply how Python garbage collects, that this may be creating extraneous intermediate objects. If you plan to use this is any sort of real code, you might want to figure that out. I did notice that if I object-chain the IMAP connection ('me' in this example), it gets dereferenced and gc'd, which invoked the very polite __del__ method, closing the connection. I'm not sure how to avoid that, so I just commented out the __del__ method, leaving a messy open connection to the server.
*** My thinking is to only go do the time-consuming fetching of messages when needed: when an email message object is referenced or when an iterator is set up (on the assumption that when you set up an iterator, you plan to consume the whole set of messages.) This latter is because fetching 100 messages in a single fetch is far faster than 100 single message fetches. The default is to only fetch the headers, except when the text itself is explicitly asked for. This default can be changed by setting priority='both' or priority='text' when you call iMapBox to open a connection to the server.